Contribution of prior semantic knowledge to new episodic learning in amnesia.
Kan, Irene P; Alexander, Michael P; Verfaellie, Mieke
2009-05-01
We evaluated whether prior semantic knowledge would enhance episodic learning in amnesia. Subjects studied prices that are either congruent or incongruent with prior price knowledge for grocery and household items and then performed a forced-choice recognition test for the studied prices. Consistent with a previous report, healthy controls' performance was enhanced by price knowledge congruency; however, only a subset of amnesic patients experienced the same benefit. Whereas patients with relatively intact semantic systems, as measured by an anatomical measure (i.e., lesion involvement of anterior and lateral temporal lobes), experienced a significant congruency benefit, patients with compromised semantic systems did not experience a congruency benefit. Our findings suggest that when prior knowledge structures are intact, they can support acquisition of new episodic information by providing frameworks into which such information can be incorporated.
A Study about Placement Support Using Semantic Similarity
ERIC Educational Resources Information Center
Katz, Marco; van Bruggen, Jan; Giesbers, Bas; Waterink, Wim; Eshuis, Jannes; Koper, Rob
2014-01-01
This paper discusses Latent Semantic Analysis (LSA) as a method for the assessment of prior learning. The Accreditation of Prior Learning (APL) is a procedure to offer learners an individualized curriculum based on their prior experiences and knowledge. The placement decisions in this process are based on the analysis of student material by domain…
Olsher, Daniel
2014-10-01
Noise-resistant and nuanced, COGBASE makes 10 million pieces of commonsense data and a host of novel reasoning algorithms available via a family of semantically-driven prior probability distributions. Machine learning, Big Data, natural language understanding/processing, and social AI can draw on COGBASE to determine lexical semantics, infer goals and interests, simulate emotion and affect, calculate document gists and topic models, and link commonsense knowledge to domain models and social, spatial, cultural, and psychological data. COGBASE is especially ideal for social Big Data, which tends to involve highly implicit contexts, cognitive artifacts, difficult-to-parse texts, and deep domain knowledge dependencies. Copyright © 2014 Elsevier Ltd. All rights reserved.
Yeari, Menahem; van den Broek, Paul
2016-09-01
It is a well-accepted view that the prior semantic (general) knowledge that readers possess plays a central role in reading comprehension. Nevertheless, computational models of reading comprehension have not integrated the simulation of semantic knowledge and online comprehension processes under a unified mathematical algorithm. The present article introduces a computational model that integrates the landscape model of comprehension processes with latent semantic analysis representation of semantic knowledge. In three sets of simulations of previous behavioral findings, the integrated model successfully simulated the activation and attenuation of predictive and bridging inferences during reading, as well as centrality estimations and recall of textual information after reading. Analyses of the computational results revealed new theoretical insights regarding the underlying mechanisms of the various comprehension phenomena.
Language knowledge and event knowledge in language use.
Willits, Jon A; Amato, Michael S; MacDonald, Maryellen C
2015-05-01
This paper examines how semantic knowledge is used in language comprehension and in making judgments about events in the world. We contrast knowledge gleaned from prior language experience ("language knowledge") and knowledge coming from prior experience with the world ("world knowledge"). In two corpus analyses, we show that previous research linking verb aspect and event representations have confounded language and world knowledge. Then, using carefully chosen stimuli that remove this confound, we performed four experiments that manipulated the degree to which language knowledge or world knowledge should be salient and relevant to performing a task, finding in each case that participants use the type of knowledge most appropriate to the task. These results provide evidence for a highly context-sensitive and interactionist perspective on how semantic knowledge is represented and used during language processing. Copyright © 2015. Published by Elsevier Inc.
Implicit Learning of Semantic Preferences of Verbs
ERIC Educational Resources Information Center
Paciorek, Albertyna; Williams, John N.
2015-01-01
Previous studies of semantic implicit learning in language have only examined learning grammatical form-meaning connections in which learning could have been supported by prior linguistic knowledge. In this study we target the domain of verb meaning, specifically semantic preferences regarding novel verbs (e.g., the preference for a novel verb to…
Language knowledge and event knowledge in language use
Willits, Jon A.; Amato, Michael S.; MacDonald, Maryellen C.
2018-01-01
This paper examines how semantic knowledge is used in language comprehension and in making judgments about events in the world. We contrast knowledge gleaned from prior language experience (“language knowledge”) and knowledge coming from prior experience with the world (“world knowledge”). In two corpus analyses, we show that previous research linking verb aspect and event representations have confounded language and world knowledge. Then, using carefully chosen stimuli that remove this confound, we performed four experiments that manipulated the degree to which language knowledge or world knowledge should be salient and relevant to performing a task, finding in each case that participants use the type of knowledge most appropriate to the task. These results provide evidence for a highly context-sensitive and interactionist perspective on how semantic knowledge is represented and used during language processing. PMID:25791750
ERIC Educational Resources Information Center
Zion-Golumbic, Elana; Kutas, Marta; Bentin, Shlomo
2010-01-01
Prior semantic knowledge facilitates episodic recognition memory for faces. To examine the neural manifestation of the interplay between semantic and episodic memory, we investigated neuroelectric dynamics during the creation (study) and the retrieval (test) of episodic memories for famous and nonfamous faces. Episodic memory effects were evident…
Structuring and extracting knowledge for the support of hypothesis generation in molecular biology
Roos, Marco; Marshall, M Scott; Gibson, Andrew P; Schuemie, Martijn; Meij, Edgar; Katrenko, Sophia; van Hage, Willem Robert; Krommydas, Konstantinos; Adriaans, Pieter W
2009-01-01
Background Hypothesis generation in molecular and cellular biology is an empirical process in which knowledge derived from prior experiments is distilled into a comprehensible model. The requirement of automated support is exemplified by the difficulty of considering all relevant facts that are contained in the millions of documents available from PubMed. Semantic Web provides tools for sharing prior knowledge, while information retrieval and information extraction techniques enable its extraction from literature. Their combination makes prior knowledge available for computational analysis and inference. While some tools provide complete solutions that limit the control over the modeling and extraction processes, we seek a methodology that supports control by the experimenter over these critical processes. Results We describe progress towards automated support for the generation of biomolecular hypotheses. Semantic Web technologies are used to structure and store knowledge, while a workflow extracts knowledge from text. We designed minimal proto-ontologies in OWL for capturing different aspects of a text mining experiment: the biological hypothesis, text and documents, text mining, and workflow provenance. The models fit a methodology that allows focus on the requirements of a single experiment while supporting reuse and posterior analysis of extracted knowledge from multiple experiments. Our workflow is composed of services from the 'Adaptive Information Disclosure Application' (AIDA) toolkit as well as a few others. The output is a semantic model with putative biological relations, with each relation linked to the corresponding evidence. Conclusion We demonstrated a 'do-it-yourself' approach for structuring and extracting knowledge in the context of experimental research on biomolecular mechanisms. The methodology can be used to bootstrap the construction of semantically rich biological models using the results of knowledge extraction processes. Models specific to particular experiments can be constructed that, in turn, link with other semantic models, creating a web of knowledge that spans experiments. Mapping mechanisms can link to other knowledge resources such as OBO ontologies or SKOS vocabularies. AIDA Web Services can be used to design personalized knowledge extraction procedures. In our example experiment, we found three proteins (NF-Kappa B, p21, and Bax) potentially playing a role in the interplay between nutrients and epigenetic gene regulation. PMID:19796406
ERIC Educational Resources Information Center
Karbon, Jacqueline C.
Using a semantic mapping technique for vocabulary instruction, a study explored how children of diverse groups bring different cultural backgrounds and prior knowledge to tasks involved in learning new words. The study was conducted in three sixth-grade classrooms--one containing rural Native American (especially Menominee) children, another…
ERIC Educational Resources Information Center
Gurlitt, Johannes; Renkl, Alexander
2010-01-01
Two experiments investigated the effects of characteristic features of concept mapping used for prior knowledge activation. Characteristic demands of concept mapping include connecting lines representing the relationships between concepts and labeling these lines, specifying the type of the semantic relationships. In the first experiment,…
Automatic event recognition and anomaly detection with attribute grammar by learning scene semantics
NASA Astrophysics Data System (ADS)
Qi, Lin; Yao, Zhenyu; Li, Li; Dong, Junyu
2007-11-01
In this paper we present a novel framework for automatic event recognition and abnormal behavior detection with attribute grammar by learning scene semantics. This framework combines learning scene semantics by trajectory analysis and constructing attribute grammar-based event representation. The scene and event information is learned automatically. Abnormal behaviors that disobey scene semantics or event grammars rules are detected. By this method, an approach to understanding video scenes is achieved. Further more, with this prior knowledge, the accuracy of abnormal event detection is increased.
Target-Oriented High-Resolution SAR Image Formation via Semantic Information Guided Regularizations
NASA Astrophysics Data System (ADS)
Hou, Biao; Wen, Zaidao; Jiao, Licheng; Wu, Qian
2018-04-01
Sparsity-regularized synthetic aperture radar (SAR) imaging framework has shown its remarkable performance to generate a feature enhanced high resolution image, in which a sparsity-inducing regularizer is involved by exploiting the sparsity priors of some visual features in the underlying image. However, since the simple prior of low level features are insufficient to describe different semantic contents in the image, this type of regularizer will be incapable of distinguishing between the target of interest and unconcerned background clutters. As a consequence, the features belonging to the target and clutters are simultaneously affected in the generated image without concerning their underlying semantic labels. To address this problem, we propose a novel semantic information guided framework for target oriented SAR image formation, which aims at enhancing the interested target scatters while suppressing the background clutters. Firstly, we develop a new semantics-specific regularizer for image formation by exploiting the statistical properties of different semantic categories in a target scene SAR image. In order to infer the semantic label for each pixel in an unsupervised way, we moreover induce a novel high-level prior-driven regularizer and some semantic causal rules from the prior knowledge. Finally, our regularized framework for image formation is further derived as a simple iteratively reweighted $\\ell_1$ minimization problem which can be conveniently solved by many off-the-shelf solvers. Experimental results demonstrate the effectiveness and superiority of our framework for SAR image formation in terms of target enhancement and clutters suppression, compared with the state of the arts. Additionally, the proposed framework opens a new direction of devoting some machine learning strategies to image formation, which can benefit the subsequent decision making tasks.
Bein, Oded; Livneh, Neta; Reggev, Niv; Gilead, Michael; Goshen-Gottstein, Yonatan; Maril, Anat
2015-01-01
A fundamental challenge in the study of learning and memory is to understand the role of existing knowledge in the encoding and retrieval of new episodic information. The importance of prior knowledge in memory is demonstrated in the congruency effect—the robust finding wherein participants display better memory for items that are compatible, rather than incompatible, with their pre-existing semantic knowledge. Despite its robustness, the mechanism underlying this effect is not well understood. In four studies, we provide evidence that demonstrates the privileged explanatory power of the elaboration-integration account over alternative hypotheses. Furthermore, we question the implicit assumption that the congruency effect pertains to the truthfulness/sensibility of a subject-predicate proposition, and show that congruency is a function of semantic relatedness between item and context words. PMID:25695759
Bein, Oded; Livneh, Neta; Reggev, Niv; Gilead, Michael; Goshen-Gottstein, Yonatan; Maril, Anat
2015-01-01
A fundamental challenge in the study of learning and memory is to understand the role of existing knowledge in the encoding and retrieval of new episodic information. The importance of prior knowledge in memory is demonstrated in the congruency effect-the robust finding wherein participants display better memory for items that are compatible, rather than incompatible, with their pre-existing semantic knowledge. Despite its robustness, the mechanism underlying this effect is not well understood. In four studies, we provide evidence that demonstrates the privileged explanatory power of the elaboration-integration account over alternative hypotheses. Furthermore, we question the implicit assumption that the congruency effect pertains to the truthfulness/sensibility of a subject-predicate proposition, and show that congruency is a function of semantic relatedness between item and context words.
Scientific Knowledge Discovery in Complex Semantic Networks of Geophysical Systems
NASA Astrophysics Data System (ADS)
Fox, P.
2012-04-01
The vast majority of explorations of the Earth's systems are limited in their ability to effectively explore the most important (often most difficult) problems because they are forced to interconnect at the data-element, or syntactic, level rather than at a higher scientific, or semantic, level. Recent successes in the application of complex network theory and algorithms to climate data, raise expectations that more general graph-based approaches offer the opportunity for new discoveries. In the past ~ 5 years in the natural sciences there has substantial progress in providing both specialists and non-specialists the ability to describe in machine readable form, geophysical quantities and relations among them in meaningful and natural ways, effectively breaking the prior syntax barrier. The corresponding open-world semantics and reasoning provide higher-level interconnections. That is, semantics provided around the data structures, using semantically-equipped tools, and semantically aware interfaces between science application components allowing for discovery at the knowledge level. More recently, formal semantic approaches to continuous and aggregate physical processes are beginning to show promise and are soon likely to be ready to apply to geoscientific systems. To illustrate these opportunities, this presentation presents two application examples featuring domain vocabulary (ontology) and property relations (named and typed edges in the graphs). First, a climate knowledge discovery pilot encoding and exploration of CMIP5 catalog information with the eventual goal to encode and explore CMIP5 data. Second, a multi-stakeholder knowledge network for integrated assessments in marine ecosystems, where the data is highly inter-disciplinary.
Incorporating linguistic knowledge for learning distributed word representations.
Wang, Yan; Liu, Zhiyuan; Sun, Maosong
2015-01-01
Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashion, which, however, do not take rich linguistic knowledge into consideration. Linguistic knowledge can be represented as either link-based knowledge or preference-based knowledge, and we propose knowledge regularized word representation models (KRWR) to incorporate these prior knowledge for learning distributed word representations. Experiment results demonstrate that our estimated word representation achieves better performance in task of semantic relatedness ranking. This indicates that our methods can efficiently encode both prior knowledge from knowledge bases and statistical knowledge from large-scale text corpora into a unified word representation model, which will benefit many tasks in text mining.
Incorporating Linguistic Knowledge for Learning Distributed Word Representations
Wang, Yan; Liu, Zhiyuan; Sun, Maosong
2015-01-01
Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashion, which, however, do not take rich linguistic knowledge into consideration. Linguistic knowledge can be represented as either link-based knowledge or preference-based knowledge, and we propose knowledge regularized word representation models (KRWR) to incorporate these prior knowledge for learning distributed word representations. Experiment results demonstrate that our estimated word representation achieves better performance in task of semantic relatedness ranking. This indicates that our methods can efficiently encode both prior knowledge from knowledge bases and statistical knowledge from large-scale text corpora into a unified word representation model, which will benefit many tasks in text mining. PMID:25874581
Concepts, Control, and Context: A Connectionist Account of Normal and Disordered Semantic Cognition
2018-01-01
Semantic cognition requires conceptual representations shaped by verbal and nonverbal experience and executive control processes that regulate activation of knowledge to meet current situational demands. A complete model must also account for the representation of concrete and abstract words, of taxonomic and associative relationships, and for the role of context in shaping meaning. We present the first major attempt to assimilate all of these elements within a unified, implemented computational framework. Our model combines a hub-and-spoke architecture with a buffer that allows its state to be influenced by prior context. This hybrid structure integrates the view, from cognitive neuroscience, that concepts are grounded in sensory-motor representation with the view, from computational linguistics, that knowledge is shaped by patterns of lexical co-occurrence. The model successfully codes knowledge for abstract and concrete words, associative and taxonomic relationships, and the multiple meanings of homonyms, within a single representational space. Knowledge of abstract words is acquired through (a) their patterns of co-occurrence with other words and (b) acquired embodiment, whereby they become indirectly associated with the perceptual features of co-occurring concrete words. The model accounts for executive influences on semantics by including a controlled retrieval mechanism that provides top-down input to amplify weak semantic relationships. The representational and control elements of the model can be damaged independently, and the consequences of such damage closely replicate effects seen in neuropsychological patients with loss of semantic representation versus control processes. Thus, the model provides a wide-ranging and neurally plausible account of normal and impaired semantic cognition. PMID:29733663
Web Video Event Recognition by Semantic Analysis From Ubiquitous Documents.
Yu, Litao; Yang, Yang; Huang, Zi; Wang, Peng; Song, Jingkuan; Shen, Heng Tao
2016-12-01
In recent years, the task of event recognition from videos has attracted increasing interest in multimedia area. While most of the existing research was mainly focused on exploring visual cues to handle relatively small-granular events, it is difficult to directly analyze video content without any prior knowledge. Therefore, synthesizing both the visual and semantic analysis is a natural way for video event understanding. In this paper, we study the problem of Web video event recognition, where Web videos often describe large-granular events and carry limited textual information. Key challenges include how to accurately represent event semantics from incomplete textual information and how to effectively explore the correlation between visual and textual cues for video event understanding. We propose a novel framework to perform complex event recognition from Web videos. In order to compensate the insufficient expressive power of visual cues, we construct an event knowledge base by deeply mining semantic information from ubiquitous Web documents. This event knowledge base is capable of describing each event with comprehensive semantics. By utilizing this base, the textual cues for a video can be significantly enriched. Furthermore, we introduce a two-view adaptive regression model, which explores the intrinsic correlation between the visual and textual cues of the videos to learn reliable classifiers. Extensive experiments on two real-world video data sets show the effectiveness of our proposed framework and prove that the event knowledge base indeed helps improve the performance of Web video event recognition.
Qiao, Hong; Li, Yinlin; Li, Fengfu; Xi, Xuanyang; Wu, Wei
2016-10-01
Recently, many biologically inspired visual computational models have been proposed. The design of these models follows the related biological mechanisms and structures, and these models provide new solutions for visual recognition tasks. In this paper, based on the recent biological evidence, we propose a framework to mimic the active and dynamic learning and recognition process of the primate visual cortex. From principle point of view, the main contributions are that the framework can achieve unsupervised learning of episodic features (including key components and their spatial relations) and semantic features (semantic descriptions of the key components), which support higher level cognition of an object. From performance point of view, the advantages of the framework are as follows: 1) learning episodic features without supervision-for a class of objects without a prior knowledge, the key components, their spatial relations and cover regions can be learned automatically through a deep neural network (DNN); 2) learning semantic features based on episodic features-within the cover regions of the key components, the semantic geometrical values of these components can be computed based on contour detection; 3) forming the general knowledge of a class of objects-the general knowledge of a class of objects can be formed, mainly including the key components, their spatial relations and average semantic values, which is a concise description of the class; and 4) achieving higher level cognition and dynamic updating-for a test image, the model can achieve classification and subclass semantic descriptions. And the test samples with high confidence are selected to dynamically update the whole model. Experiments are conducted on face images, and a good performance is achieved in each layer of the DNN and the semantic description learning process. Furthermore, the model can be generalized to recognition tasks of other objects with learning ability.
Transient medial prefrontal perturbation reduces false memory formation.
Berkers, Ruud M W J; van der Linden, Marieke; de Almeida, Rafael F; Müller, Nils C J; Bovy, Leonore; Dresler, Martin; Morris, Richard G M; Fernández, Guillén
2017-03-01
Knowledge extracted across previous experiences, or schemas, benefit encoding and retention of congruent information. However, they can also reduce specificity and augment memory for semantically related, but false information. A demonstration of the latter is given by the Deese-Roediger-McDermott (DRM) paradigm, where the studying of words that fit a common semantic schema are found to induce false memories for words that are congruent with the given schema, but were not studied. The medial prefrontal cortex (mPFC) has been ascribed the function of leveraging prior knowledge to influence encoding and retrieval, based on imaging and patient studies. Here, we used transcranial magnetic stimulation (TMS) to transiently perturb ongoing mPFC processing immediately before participants performed the DRM-task. We observed the predicted reduction in false recall of critical lures after mPFC perturbation, compared to two control groups, whereas veridical recall and recognition memory performance remained similar across groups. These data provide initial causal evidence for a role of the mPFC in biasing the assimilation of new memories and their consolidation as a function of prior knowledge. Copyright © 2016 Elsevier Ltd. All rights reserved.
Zion-Golumbic, Elana; Kutas, Marta; Bentin, Shlomo
2010-02-01
Prior semantic knowledge facilitates episodic recognition memory for faces. To examine the neural manifestation of the interplay between semantic and episodic memory, we investigated neuroelectric dynamics during the creation (study) and the retrieval (test) of episodic memories for famous and nonfamous faces. Episodic memory effects were evident in several EEG frequency bands: theta (4-8 Hz), alpha (9-13 Hz), and gamma (40-100 Hz). Activity in these bands was differentially modulated by preexisting semantic knowledge and by episodic memory, implicating their different functional roles in memory. More specifically, theta activity and alpha suppression were larger for old compared to new faces at test regardless of fame, but were both larger for famous faces during study. This pattern of selective semantic effects suggests that the theta and alpha responses, which are primarily associated with episodic memory, reflect utilization of semantic information only when it is beneficial for task performance. In contrast, gamma activity decreased between the first (study) and second (test) presentation of a face, but overall was larger for famous than nonfamous faces. Hence, the gamma rhythm seems to be primarily related to activation of preexisting neural representations that may contribute to the formation of new episodic traces. Taken together, these data provide new insights into the complex interaction between semantic and episodic memory for faces and the neural dynamics associated with mnemonic processes.
Effects of perceptual similarity but not semantic association on false recognition in aging
Gill, Emma
2017-01-01
This study investigated semantic and perceptual influences on false recognition in older and young adults in a variant on the Deese-Roediger-McDermott paradigm. In two experiments, participants encoded intermixed sets of semantically associated words, and sets of unrelated words. Each set was presented in a shared distinctive font. Older adults were no more likely to falsely recognize semantically associated lure words compared to unrelated lures also presented in studied fonts. However, they showed an increase in false recognition of lures which were related to studied items only by a shared font. This increased false recognition was associated with recollective experience. The data show that older adults do not always rely more on prior knowledge in episodic memory tasks. They converge with other findings suggesting that older adults may also be more prone to perceptually-driven errors. PMID:29302398
Right fusiform response patterns reflect visual object identity rather than semantic similarity.
Bruffaerts, Rose; Dupont, Patrick; De Grauwe, Sophie; Peeters, Ronald; De Deyne, Simon; Storms, Gerrit; Vandenberghe, Rik
2013-12-01
We previously reported the neuropsychological consequences of a lesion confined to the middle and posterior part of the right fusiform gyrus (case JA) causing a partial loss of knowledge of visual attributes of concrete entities in the absence of category-selectivity (animate versus inanimate). We interpreted this in the context of a two-step model that distinguishes structural description knowledge from associative-semantic processing and implicated the lesioned area in the former process. To test this hypothesis in the intact brain, multi-voxel pattern analysis was used in a series of event-related fMRI studies in a total of 46 healthy subjects. We predicted that activity patterns in this region would be determined by the identity of rather than the conceptual similarity between concrete entities. In a prior behavioral experiment features were generated for each entity by more than 1000 subjects. Based on a hierarchical clustering analysis the entities were organised into 3 semantic clusters (musical instruments, vehicles, tools). Entities were presented as words or pictures. With foveal presentation of pictures, cosine similarity between fMRI response patterns in right fusiform cortex appeared to reflect both the identity of and the semantic similarity between the entities. No such effects were found for words in this region. The effect of object identity was invariant for location, scaling, orientation axis and color (grayscale versus color). It also persisted for different exemplars referring to a same concrete entity. The apparent semantic similarity effect however was not invariant. This study provides further support for a neurobiological distinction between structural description knowledge and processing of semantic relationships and confirms the role of right mid-posterior fusiform cortex in the former process, in accordance with previous lesion evidence. © 2013.
Hsu, Patty; Taylor, J Eric T; Pratt, Jay
2015-01-01
The Ternus effect is a robust illusion of motion that produces element motion at short interstimulus intervals (ISIs; < 50 ms) and group motion at longer ISIs (> 50 ms). Previous research has shown that the nature of the stimuli (e.g., similarity, grouping), not just ISI, can influence the likelihood of perceiving element or group motion. We examined if semantic knowledge can also influence what type of illusory motion is perceived. In Experiment I, we used a modified Ternus display with pictures of frogs in a jump-ready pose facing forwards or backwards to the direction of illusory motion. Participants perceived more element motion with the forward-facing frogs and more group motion with the backward-facing frogs. Experiment 2 tested whether this effect would still occur with line drawings of frogs, or if a more life-like image was necessary. Experiment 3 tested whether this effect was due to visual asymmetries inherent in the jumping pose. Experiment 4 tested whether frogs in a "non-jumping," sedentary pose would replicate the original effect. These experiments elucidate the role of semantic knowledge in the Ternus effect. Prior knowledge of the movement of certain animate objects, in this case, frogs can also bias the perception of element or group motion.
Morson, Suzannah M; Moulin, Chris J A; Souchay, Céline
2015-05-01
Failure to recall an item from memory can be accompanied by the subjective experience that the item is known but currently unavailable for report. The feeling of knowing (FOK) task allows measurement of the predictive accuracy of this reflective judgement. Young and older adults were asked to provide answers to general knowledge questions both prior to and after learning, thus measuring both semantic and episodic memory for the items. FOK judgements were made at each stage for all unrecalled responses, providing a measure of predictive accuracy for semantic and episodic knowledge. Results demonstrated a selective effect of age on episodic FOK resolution, with older adults found to have impaired episodic FOK accuracy while semantic FOK accuracy remained intact. Although recall and recognition measures of episodic memory are equivalent between the two age groups, older adults may have been unable to access contextual details on which to base their FOK judgements. The results suggest that older adults are not able to accurately predict future recognition of unrecalled episodic information, and consequently may have difficulties in monitoring recently encoded memories. Copyright © 2015. Published by Elsevier B.V.
Robinson, Sally J; Temple, Christine M
2013-04-01
This paper addresses the relative independence of different types of lexical- and factually-based semantic knowledge in JM, a 9-year-old boy with Klinefelter syndrome (KS). JM was matched to typically developing (TD) controls on the basis of chronological age. Lexical-semantic knowledge was investigated for common noun (CN) and mathematical vocabulary items (MV). Factually-based semantic knowledge was investigated for general and number facts. For CN items, JM's lexical stores were of a normal size but the volume of correct 'sensory feature' semantic knowledge he generated within verbal item descriptions was significantly reduced. He was also significantly impaired at naming item descriptions and pictures, particularly for fruit and vegetables. There was also weak object decision for fruit and vegetables. In contrast, for MV items, JM's lexical stores were elevated, with no significant difference in the amount and type of correct semantic knowledge generated within verbal item descriptions and normal naming. JM's fact retrieval accuracy was normal for all types of factual knowledge. JM's performance indicated a dissociation between the representation of CN and MV vocabulary items during development. JM's preserved semantic knowledge of facts in the face of impaired semantic knowledge of vocabulary also suggests that factually-based semantic knowledge representation is not dependent on normal lexical-semantic knowledge during development. These findings are discussed in relation to the emergence of distinct semantic knowledge representations during development, due to differing degrees of dependency upon the acquisition and representation of semantic knowledge from verbal propositions and perceptual input.
Virtual reality training improves students' knowledge structures of medical concepts.
Stevens, Susan M; Goldsmith, Timothy E; Summers, Kenneth L; Sherstyuk, Andrei; Kihmm, Kathleen; Holten, James R; Davis, Christopher; Speitel, Daniel; Maris, Christina; Stewart, Randall; Wilks, David; Saland, Linda; Wax, Diane; Panaiotis; Saiki, Stanley; Alverson, Dale; Caudell, Thomas P
2005-01-01
Virtual environments can provide training that is difficult to achieve under normal circumstances. Medical students can work on high-risk cases in a realistic, time-critical environment, where students practice skills in a cognitively demanding and emotionally compelling situation. Research from cognitive science has shown that as students acquire domain expertise, their semantic organization of core domain concepts become more similar to those of an expert's. In the current study, we hypothesized that students' knowledge structures would become more expert-like as a result of their diagnosing and treating a patient experiencing a hematoma within a virtual environment. Forty-eight medical students diagnosed and treated a hematoma case within a fully immersed virtual environment. Student's semantic organization of 25 case-related concepts was assessed prior to and after training. Students' knowledge structures became more integrated and similar to an expert knowledge structure of the concepts as a result of the learning experience. The methods used here for eliciting, representing, and evaluating knowledge structures offer a sensitive and objective means for evaluating student learning in virtual environments and medical simulations.
Hoffman, Paul
2018-05-25
Semantic cognition refers to the appropriate use of acquired knowledge about the world. This requires representation of knowledge as well as control processes which ensure that currently-relevant aspects of knowledge are retrieved and selected. Although these abilities can be impaired selectively following brain damage, the relationship between them in healthy individuals is unclear. It is also commonly assumed that semantic cognition is preserved in later life, because older people have greater reserves of knowledge. However, this claim overlooks the possibility of decline in semantic control processes. Here, semantic cognition was assessed in 100 young and older adults. Despite having a broader knowledge base, older people showed specific impairments in semantic control, performing more poorly than young people when selecting among competing semantic representations. Conversely, they showed preserved controlled retrieval of less salient information from the semantic store. Breadth of semantic knowledge was positively correlated with controlled retrieval but was unrelated to semantic selection ability, which was instead correlated with non-semantic executive function. These findings indicate that three distinct elements contribute to semantic cognition: semantic representations that accumulate throughout the lifespan, processes for controlled retrieval of less salient semantic information, which appear age-invariant, and mechanisms for selecting task-relevant aspects of semantic knowledge, which decline with age and may relate more closely to domain-general executive control.
Estmacott, Robyn W; Moscovitch, Morris
2002-03-01
The consolidation theory of long-term memory (e.g., Squire, 1992) predicts that damage to the medial temporal lobes will result in temporally graded retrograde memory loss, with a disproportionate impairment of recent relative to remote knowledge; in contrast, severe atrophy of the temporal neocortex is predicted to result in the reverse temporally graded pattern, with a selective sparing of recent memory (K.S. Graham & Hodges, 1997). Previously, we reported evidence that autobiographical episodic memory does not follow this temporal pattern (Westmacott, Leach, Freedman, & Moscovitch, 2001). In the present study, we found evidence suggesting that semantic memory loss does follow the predicted temporal pattern. We used a set of tasks that tap implicit and explicit memory for famous names and English vocabulary terms from across the 20th century. KC, a person with medial temporal amnesia, consistently demonstrated across tasks a selective deficit for famous names and vocabulary terms from the 5-year period just prior to injury; this deficit was particularly profound for elaborated semantic knowledge (e.g., word definitions, occupation of famous person). However, when asked to guess on unfamiliar items, KC's performance for names and words from this 5-year time period increased substantially, suggesting that he retains some of this knowledge at an implicit or rudimentary level. Conversely, EL, a semantic dementia patient with temporal neocortical atrophy and relative sparing of the medial temporal lobe, demonstrated a selective sparing of names and words from the most recent time period. However, this selective sparing of recent semantic memory was demonstrated in the implicit tasks only; performance on explicit tasks suggested an equally severe impairment of semantics across all time periods. Unlike the data from our previous study of autobiographical episodic memory, these findings are consistent with the predictions both of consolidation theory (Hodges & Graham, 1998; Squire, 1992) and multiple trace theory (Nadel & Moscovitch, 1999) that the hippocampus plays a timelimited role in the acquisition and representation of long-term semantic memories. Moreover, our findings suggest that tasks requiring minimal verbal production and explicit recall may provide a more sensitive and comprehensive assessment of intact memory capacity in brain-damaged individuals.
Ekstrand, Chelsea; Neudorf, Josh; Lorentz, Eric; Gould, Layla; Mickleborough, Marla; Borowsky, Ron
2017-11-01
Prevalent theories of semantic processing assert that the sensorimotor system plays a functional role in the semantic processing of manipulable objects. While motor execution has been shown to impact object processing, involvement of the somatosensory system has remained relatively unexplored. Therefore, we developed two novel priming paradigms. In Experiment 1, participants received a vibratory hand prime (on half the trials) prior to viewing a picture of either an object interacted primarily with the hand (e.g., a cup) or the foot (e.g., a soccer ball) and reported how they would interact with it. In Experiment 2, the same objects became the prime and participants were required to identify whether the vibratory stimulation occurred to their hand or foot. In both experiments, somatosensory priming effects arose for the hand objects, while foot objects showed no priming benefits. These results suggest that object semantic knowledge bidirectionally converges with the somatosensory system. Copyright © 2017 Elsevier B.V. All rights reserved.
Lloyd-Jones, Toby J; Nakabayashi, Kazuyo
2014-01-01
Using a novel paradigm to engage the long-term mappings between object names and the prototypical colors for objects, we investigated the retrieval of object-color knowledge as indexed by long-term priming (the benefit in performance from a prior encounter with the same or a similar stimulus); a process about which little is known. We examined priming from object naming on a lexical-semantic matching task. In the matching task participants encountered a visually presented object name (Experiment 1) or object shape (Experiment 2) paired with either a color patch or color name. The pairings could either match whereby both were consistent with a familiar object (e.g., strawberry and red) or mismatch (strawberry and blue). We used the matching task to probe knowledge about familiar objects and their colors pre-activated during object naming. In particular, we examined whether the retrieval of object-color information was modality-specific and whether this influenced priming. Priming varied with the nature of the retrieval process: object-color priming arose for object names but not object shapes and beneficial effects of priming were observed for color patches whereas inhibitory priming arose with color names. These findings have implications for understanding how object knowledge is retrieved from memory and modified by learning.
Knowledge of the human body: a distinct semantic domain.
Coslett, H Branch; Saffran, Eleanor M; Schwoebel, John
2002-08-13
Patients with selective deficits in the naming and comprehension of animals, plants, and artifacts have been reported. These descriptions of specific semantic category deficits have contributed substantially to the understanding of the architecture of semantic representations. This study sought to further understanding of the organization of the semantic system by demonstrating that another semantic category, knowledge of the human body, may be selectively preserved. The performance of a patient with semantic dementia was compared with the performance of healthy controls on a variety of tasks assessing distinct types of body representations, including the body schema, body image, and body structural description. Despite substantial deficits on tasks involving language and knowledge of the world generally, the patient performed normally on all tests of body knowledge except body part naming; even in this naming task, however, her performance with body parts was significantly better than on artifacts. The demonstration that body knowledge may be preserved despite substantial semantic deficits involving other types of semantic information argues that body knowledge is a distinct and dissociable semantic category. These data are interpreted as support for a model of semantics that proposes that knowledge is distributed across different cortical regions reflecting the manner in which the information was acquired.
Arbitrary Symbolism in Natural Language Revisited: When Word Forms Carry Meaning
Reilly, Jamie; Westbury, Chris; Kean, Jacob; Peelle, Jonathan E.
2012-01-01
Cognitive science has a rich history of interest in the ways that languages represent abstract and concrete concepts (e.g., idea vs. dog). Until recently, this focus has centered largely on aspects of word meaning and semantic representation. However, recent corpora analyses have demonstrated that abstract and concrete words are also marked by phonological, orthographic, and morphological differences. These regularities in sound-meaning correspondence potentially allow listeners to infer certain aspects of semantics directly from word form. We investigated this relationship between form and meaning in a series of four experiments. In Experiments 1–2 we examined the role of metalinguistic knowledge in semantic decision by asking participants to make semantic judgments for aurally presented nonwords selectively varied by specific acoustic and phonetic parameters. Participants consistently associated increased word length and diminished wordlikeness with abstract concepts. In Experiment 3, participants completed a semantic decision task (i.e., abstract or concrete) for real words varied by length and concreteness. Participants were more likely to misclassify longer, inflected words (e.g., “apartment”) as abstract and shorter uninflected abstract words (e.g., “fate”) as concrete. In Experiment 4, we used a multiple regression to predict trial level naming data from a large corpus of nouns which revealed significant interaction effects between concreteness and word form. Together these results provide converging evidence for the hypothesis that listeners map sound to meaning through a non-arbitrary process using prior knowledge about statistical regularities in the surface forms of words. PMID:22879931
Arbitrary symbolism in natural language revisited: when word forms carry meaning.
Reilly, Jamie; Westbury, Chris; Kean, Jacob; Peelle, Jonathan E
2012-01-01
Cognitive science has a rich history of interest in the ways that languages represent abstract and concrete concepts (e.g., idea vs. dog). Until recently, this focus has centered largely on aspects of word meaning and semantic representation. However, recent corpora analyses have demonstrated that abstract and concrete words are also marked by phonological, orthographic, and morphological differences. These regularities in sound-meaning correspondence potentially allow listeners to infer certain aspects of semantics directly from word form. We investigated this relationship between form and meaning in a series of four experiments. In Experiments 1-2 we examined the role of metalinguistic knowledge in semantic decision by asking participants to make semantic judgments for aurally presented nonwords selectively varied by specific acoustic and phonetic parameters. Participants consistently associated increased word length and diminished wordlikeness with abstract concepts. In Experiment 3, participants completed a semantic decision task (i.e., abstract or concrete) for real words varied by length and concreteness. Participants were more likely to misclassify longer, inflected words (e.g., "apartment") as abstract and shorter uninflected abstract words (e.g., "fate") as concrete. In Experiment 4, we used a multiple regression to predict trial level naming data from a large corpus of nouns which revealed significant interaction effects between concreteness and word form. Together these results provide converging evidence for the hypothesis that listeners map sound to meaning through a non-arbitrary process using prior knowledge about statistical regularities in the surface forms of words.
Finding gene regulatory network candidates using the gene expression knowledge base.
Venkatesan, Aravind; Tripathi, Sushil; Sanz de Galdeano, Alejandro; Blondé, Ward; Lægreid, Astrid; Mironov, Vladimir; Kuiper, Martin
2014-12-10
Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of 'omics' data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis. We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions. Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.
Action and semantic tool knowledge - Effective connectivity in the underlying neural networks.
Kleineberg, Nina N; Dovern, Anna; Binder, Ellen; Grefkes, Christian; Eickhoff, Simon B; Fink, Gereon R; Weiss, Peter H
2018-04-26
Evidence from neuropsychological and imaging studies indicate that action and semantic knowledge about tools draw upon distinct neural substrates, but little is known about the underlying interregional effective connectivity. With fMRI and dynamic causal modeling (DCM) we investigated effective connectivity in the left-hemisphere (LH) while subjects performed (i) a function knowledge and (ii) a value knowledge task, both addressing semantic tool knowledge, and (iii) a manipulation (action) knowledge task. Overall, the results indicate crosstalk between action nodes and semantic nodes. Interestingly, effective connectivity was weakened between semantic nodes and action nodes during the manipulation task. Furthermore, pronounced modulations of effective connectivity within the fronto-parietal action system of the LH (comprising lateral occipito-temporal cortex, intraparietal sulcus, supramarginal gyrus, inferior frontal gyrus) were observed in a bidirectional manner during the processing of action knowledge. In contrast, the function and value knowledge tasks resulted in a significant strengthening of the effective connectivity between visual cortex and fusiform gyrus. Importantly, this modulation was present in both semantic tasks, indicating that processing different aspects of semantic knowledge about tools evokes similar effective connectivity patterns. Data revealed that interregional effective connectivity during the processing of tool knowledge occurred in a bidirectional manner with a weakening of connectivity between areas engaged in action and semantic knowledge about tools during the processing of action knowledge. Moreover, different semantic tool knowledge tasks elicited similar effective connectivity patterns. © 2018 Wiley Periodicals, Inc.
Loaiza, Vanessa M; Rhodes, Matthew G; Anglin, Julia
2015-09-01
The assumption that working memory (WM) is embedded within long-term memory suggests that the effectiveness of switching information between activated states in WM (i.e., attentional refreshing) may depend on whether that information is semantically relevant. Given that older adults often have greater general knowledge than younger adults, age-related deficits in episodic memory (EM) could be ameliorated by studying information that has existing semantic representations compared with unknown information. Younger and older adults completed a modified operation span task that varied the number of refreshing opportunities. The memoranda used were equally known to younger and older adults (neutral words; e.g., father), better known to older adults than younger adults (dated words; e.g., mirth), or unknown to both groups (unknown words; e.g., cobot). Results for immediate and delayed recall indicated an age-related improvement for dated memoranda and no age difference for unknown memoranda. Furthermore, refreshing opportunities predicted delayed recall of neutral memoranda more strongly for younger adults than older adults, whereas older adults' recall advantage for dated memoranda was explained by their prior knowledge and not refreshing opportunities. The results suggest that older adults' EM deficits could potentially be ameliorated by incorporating their superior knowledge to supplement relatively ineffective attentional refreshing in WM. © The Author 2013. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Knowledge acquisition is governed by striatal prediction errors.
Pine, Alex; Sadeh, Noa; Ben-Yakov, Aya; Dudai, Yadin; Mendelsohn, Avi
2018-04-26
Discrepancies between expectations and outcomes, or prediction errors, are central to trial-and-error learning based on reward and punishment, and their neurobiological basis is well characterized. It is not known, however, whether the same principles apply to declarative memory systems, such as those supporting semantic learning. Here, we demonstrate with fMRI that the brain parametrically encodes the degree to which new factual information violates expectations based on prior knowledge and beliefs-most prominently in the ventral striatum, and cortical regions supporting declarative memory encoding. These semantic prediction errors determine the extent to which information is incorporated into long-term memory, such that learning is superior when incoming information counters strong incorrect recollections, thereby eliciting large prediction errors. Paradoxically, by the same account, strong accurate recollections are more amenable to being supplanted by misinformation, engendering false memories. These findings highlight a commonality in brain mechanisms and computational rules that govern declarative and nondeclarative learning, traditionally deemed dissociable.
Joubert, Sven; Brambati, Simona M; Ansado, Jennyfer; Barbeau, Emmanuel J; Felician, Olivier; Didic, Mira; Lacombe, Jacinthe; Goldstein, Rachel; Chayer, Céline; Kergoat, Marie-Jeanne
2010-03-01
Semantic deficits in Alzheimer's disease have been widely documented, but little is known about the integrity of semantic memory in the prodromal stage of the illness. The aims of the present study were to: (i) investigate naming abilities and semantic memory in amnestic mild cognitive impairment (aMCI), early Alzheimer's disease (AD) compared to healthy older subjects; (ii) investigate the association between naming and semantic knowledge in aMCI and AD; (iii) examine if the semantic impairment was present in different modalities; and (iv) study the relationship between semantic performance and grey matter volume using voxel-based morphometry. Results indicate that both naming and semantic knowledge of objects and famous people were impaired in aMCI and early AD groups, when compared to healthy age- and education-matched controls. Item-by-item analyses showed that anomia in aMCI and early AD was significantly associated with underlying semantic knowledge of famous people but not with semantic knowledge of objects. Moreover, semantic knowledge of the same concepts was impaired in both the visual and the verbal modalities. Finally, voxel-based morphometry analyses revealed that semantic impairment in aMCI and AD was associated with cortical atrophy in the anterior temporal lobe (ATL) region as well as in the inferior prefrontal cortex (IPC), some of the key regions of the semantic cognition network. These findings suggest that the semantic impairment in aMCI may result from a breakdown of semantic knowledge of famous people and objects, combined with difficulties in the selection, manipulation and retrieval of this knowledge. Copyright (c) 2009 Elsevier Ltd. All rights reserved.
ERIC Educational Resources Information Center
Beal-Alvarez, Jennifer S.; Figueroa, Daileen M.
2017-01-01
Two key areas of language development include semantic and phonological knowledge. Semantic knowledge relates to word and concept knowledge. Phonological knowledge relates to how language parameters combine to create meaning. We investigated signing deaf adults' and children's semantic and phonological sign generation via one-minute tasks,…
Figure-ground segmentation based on class-independent shape priors
NASA Astrophysics Data System (ADS)
Li, Yang; Liu, Yang; Liu, Guojun; Guo, Maozu
2018-01-01
We propose a method to generate figure-ground segmentation by incorporating shape priors into the graph-cuts algorithm. Given an image, we first obtain a linear representation of an image and then apply directional chamfer matching to generate class-independent, nonparametric shape priors, which provide shape clues for the graph-cuts algorithm. We then enforce shape priors in a graph-cuts energy function to produce object segmentation. In contrast to previous segmentation methods, the proposed method shares shape knowledge for different semantic classes and does not require class-specific model training. Therefore, the approach obtains high-quality segmentation for objects. We experimentally validate that the proposed method outperforms previous approaches using the challenging PASCAL VOC 2010/2012 and Berkeley (BSD300) segmentation datasets.
Tanguay, Annick N; Benton, Lauren; Romio, Lorenza; Sievers, Carolin; Davidson, Patrick S R; Renoult, Louis
2018-02-01
Self-knowledge concerns one's own preferences and personality. It pertains to the self (similar to episodic memory), yet does not concern events. It is factual (like semantic memory), but also idiosyncratic. For these reasons, it is unclear where self-knowledge might fall on a continuum in relation to semantic and episodic memory. In this study, we aimed to compare the event-related potential (ERP) correlates of self-knowledge to those of semantic and episodic memory, using N400 and Late Positive Component (LPC) as proxies for semantic and episodic processing, respectively. We considered an additional factor: time perspective. Temporally distant selves have been suggested to be more semantic compared to the present self, but thinking about one's past and future selves may also engage episodic memory. Twenty-eight adults answered whether traits (e.g., persistent) were true of most people holding an occupation (e.g., soldiers; semantic memory condition), or true of themselves 5 years ago, in the present, or 5 years from now (past, present, and future self-knowledge conditions). The study ended with an episodic recognition memory task for previously seen traits. Present self-knowledge produced mean LPC amplitudes at posterior parietal sites that fell between semantic and episodic memory. Mean LPC amplitudes for past and future self-knowledge were greater than for semantic memory, and not significantly different from episodic memory. Mean N400 amplitudes for the self-knowledge conditions were smaller than for semantic memory at sagittal sites. However, this N400 effect was not separable from a preceding P200 effect at these same electrode sites. This P200 effect can be interpreted as reflecting the greater emotional salience of self as compared to general knowledge, which may have facilitated semantic processing. Overall, our findings are consistent with a distinction between knowledge of others and self-knowledge, but the closeness of self-knowledge's neural correlates to either semantic or episodic memory appears to depend to some extent on time perspective. Copyright © 2017 Elsevier Ltd. All rights reserved.
ERIC Educational Resources Information Center
Lytras, Miltiadis, Ed.; Naeve, Ambjorn, Ed.
2005-01-01
In the context of Knowledge Society, the convergence of knowledge and learning management is a critical milestone. "Intelligent Learning Infrastructure for Knowledge Intensive Organizations: A Semantic Web Perspective" provides state-of-the art knowledge through a balanced theoretical and technological discussion. The semantic web perspective…
Semantic memory in object use.
Silveri, Maria Caterina; Ciccarelli, Nicoletta
2009-10-01
We studied five patients with semantic memory disorders, four with semantic dementia and one with herpes simplex virus encephalitis, to investigate the involvement of semantic conceptual knowledge in object use. Comparisons between patients who had semantic deficits of different severity, as well as the follow-up, showed that the ability to use objects was largely preserved when the deficit was mild but progressively decayed as the deficit became more severe. Naming was generally more impaired than object use. Production tasks (pantomime execution and actual object use) and comprehension tasks (pantomime recognition and action recognition) as well as functional knowledge about objects were impaired when the semantic deficit was severe. Semantic and unrelated errors were produced during object use, but actions were always fluent and patients performed normally on a novel tools task in which the semantic demand was minimal. Patients with severe semantic deficits scored borderline on ideational apraxia tasks. Our data indicate that functional semantic knowledge is crucial for using objects in a conventional way and suggest that non-semantic factors, mainly non-declarative components of memory, might compensate to some extent for semantic disorders and guarantee some residual ability to use very common objects independently of semantic knowledge.
Lloyd-Jones, Toby J.; Nakabayashi, Kazuyo
2014-01-01
Using a novel paradigm to engage the long-term mappings between object names and the prototypical colors for objects, we investigated the retrieval of object-color knowledge as indexed by long-term priming (the benefit in performance from a prior encounter with the same or a similar stimulus); a process about which little is known. We examined priming from object naming on a lexical-semantic matching task. In the matching task participants encountered a visually presented object name (Experiment 1) or object shape (Experiment 2) paired with either a color patch or color name. The pairings could either match whereby both were consistent with a familiar object (e.g., strawberry and red) or mismatch (strawberry and blue). We used the matching task to probe knowledge about familiar objects and their colors pre-activated during object naming. In particular, we examined whether the retrieval of object-color information was modality-specific and whether this influenced priming. Priming varied with the nature of the retrieval process: object-color priming arose for object names but not object shapes and beneficial effects of priming were observed for color patches whereas inhibitory priming arose with color names. These findings have implications for understanding how object knowledge is retrieved from memory and modified by learning. PMID:25009522
A Bayesian generative model for learning semantic hierarchies
Mittelman, Roni; Sun, Min; Kuipers, Benjamin; Savarese, Silvio
2014-01-01
Building fine-grained visual recognition systems that are capable of recognizing tens of thousands of categories, has received much attention in recent years. The well known semantic hierarchical structure of categories and concepts, has been shown to provide a key prior which allows for optimal predictions. The hierarchical organization of various domains and concepts has been subject to extensive research, and led to the development of the WordNet domains hierarchy (Fellbaum, 1998), which was also used to organize the images in the ImageNet (Deng et al., 2009) dataset, in which the category count approaches the human capacity. Still, for the human visual system, the form of the hierarchy must be discovered with minimal use of supervision or innate knowledge. In this work, we propose a new Bayesian generative model for learning such domain hierarchies, based on semantic input. Our model is motivated by the super-subordinate organization of domain labels and concepts that characterizes WordNet, and accounts for several important challenges: maintaining context information when progressing deeper into the hierarchy, learning a coherent semantic concept for each node, and modeling uncertainty in the perception process. PMID:24904452
Liberal Entity Extraction: Rapid Construction of Fine-Grained Entity Typing Systems.
Huang, Lifu; May, Jonathan; Pan, Xiaoman; Ji, Heng; Ren, Xiang; Han, Jiawei; Zhao, Lin; Hendler, James A
2017-03-01
The ability of automatically recognizing and typing entities in natural language without prior knowledge (e.g., predefined entity types) is a major challenge in processing such data. Most existing entity typing systems are limited to certain domains, genres, and languages. In this article, we propose a novel unsupervised entity-typing framework by combining symbolic and distributional semantics. We start from learning three types of representations for each entity mention: general semantic representation, specific context representation, and knowledge representation based on knowledge bases. Then we develop a novel joint hierarchical clustering and linking algorithm to type all mentions using these representations. This framework does not rely on any annotated data, predefined typing schema, or handcrafted features; therefore, it can be quickly adapted to a new domain, genre, and/or language. Experiments on genres (news and discussion forum) show comparable performance with state-of-the-art supervised typing systems trained from a large amount of labeled data. Results on various languages (English, Chinese, Japanese, Hausa, and Yoruba) and domains (general and biomedical) demonstrate the portability of our framework.
Liberal Entity Extraction: Rapid Construction of Fine-Grained Entity Typing Systems
Huang, Lifu; May, Jonathan; Pan, Xiaoman; Ji, Heng; Ren, Xiang; Han, Jiawei; Zhao, Lin; Hendler, James A.
2017-01-01
Abstract The ability of automatically recognizing and typing entities in natural language without prior knowledge (e.g., predefined entity types) is a major challenge in processing such data. Most existing entity typing systems are limited to certain domains, genres, and languages. In this article, we propose a novel unsupervised entity-typing framework by combining symbolic and distributional semantics. We start from learning three types of representations for each entity mention: general semantic representation, specific context representation, and knowledge representation based on knowledge bases. Then we develop a novel joint hierarchical clustering and linking algorithm to type all mentions using these representations. This framework does not rely on any annotated data, predefined typing schema, or handcrafted features; therefore, it can be quickly adapted to a new domain, genre, and/or language. Experiments on genres (news and discussion forum) show comparable performance with state-of-the-art supervised typing systems trained from a large amount of labeled data. Results on various languages (English, Chinese, Japanese, Hausa, and Yoruba) and domains (general and biomedical) demonstrate the portability of our framework. PMID:28328252
Developmental amnesia: a new pattern of dissociation with intact episodic memory.
Temple, Christine M; Richardson, Paul
2004-01-01
A case of developmental amnesia is reported for a child, CL, of normal intelligence, who has intact episodic memory but impaired semantic memory for both semantic knowledge of facts and semantic knowledge of words, including general world knowledge, knowledge of word meanings and superordinate knowledge of words. In contrast to the deficits in semantic memory, there are no impairments in episodic memory for verbal or visual material, assessed by recall or recognition. Lexical decision was also intact, indicating impairment in semantic knowledge of vocabulary rather than absence of lexical representations. The case forms a double dissociation to the cases of Vargha-Khadem et al. [Science 277 (1997) 376; Episodic memory: new directions in research (2002) 153]; Gadian et al. [Brain 123 (2000) 499] for whom semantic memory was intact but episodic memory was impaired. This double dissociation suggests that semantic memory and episodic memory have the capacity to develop separately and supports models of modularity within memory development and a functional architecture for the developmental disorders within which there is residual normality rather than pervasive abnormality. Knowledge of arithmetical facts is also spared for CL, consistent with adult studies arguing for numeracy knowledge distinct from other semantics. Reading was characterised by difficulty with irregular words and homophones but intact reading of nonwords. CL has surface dyslexia with poor lexico-semantic reading skills but good phonological reading skills. The case was identified following screening from a population of normal schoolchildren suggesting that developmental amnesias may be more pervasive than has been recognised previously.
Cousins, Katheryn A Q; Grossman, Murray
2017-12-01
Category-specific impairments caused by brain damage can provide important insights into how semantic concepts are organized in the brain. Recent research has demonstrated that disease to sensory and motor cortices can impair perceptual feature knowledge important to the representation of semantic concepts. This evidence supports the grounded cognition theory of semantics, the view that lexical knowledge is partially grounded in perceptual experience and that sensory and motor regions support semantic representations. Less well understood, however, is how heteromodal semantic hubs work to integrate and process semantic information. Although the majority of semantic research to date has focused on how sensory cortical areas are important for the representation of semantic features, new research explores how semantic memory is affected by neurodegeneration in regions important for semantic processing. Here, we review studies that demonstrate impairments to abstract noun knowledge in behavioural variant frontotemporal degeneration (bvFTD) and to action verb knowledge in Parkinson's disease, and discuss how these deficits relate to disease of the semantic selection network. Findings demonstrate that semantic selection processes are supported by the left inferior frontal gyrus (LIFG) and basal ganglia, and that disease to these regions in bvFTD and Parkinson's disease can lead to categorical impairments for abstract nouns and action verbs, respectively.
Verb Production during Action Naming in Semantic Dementia
ERIC Educational Resources Information Center
Meligne, D.; Fossard, M.; Belliard, S.; Moreaud, O.; Duvignau, K.; Demonet, J.-F.
2011-01-01
In contrast with widely documented deficits of semantic knowledge relating to object concepts and the corresponding nouns in semantic dementia (SD), little is known about action semantics and verb production in SD. The degradation of action semantic knowledge was studied in 5 patients with SD compared with 17 matched control participants in an…
Memory integration in amnesia: prior knowledge supports verbal short-term memory.
Race, Elizabeth; Palombo, Daniela J; Cadden, Margaret; Burke, Keely; Verfaellie, Mieke
2015-04-01
Short-term memory (STM) and long-term memory (LTM) have traditionally been considered cognitively distinct. However, it is known that STM can improve when to-be-remembered information appears in contexts that make contact with prior knowledge, suggesting a more interactive relationship between STM and LTM. The current study investigated whether the ability to leverage LTM in support of STM critically depends on the integrity of the hippocampus. Specifically, we investigated whether the hippocampus differentially supports between-domain versus within-domain STM-LTM integration given prior evidence that the representational domain of the elements being integrated in memory is a critical determinant of whether memory performance depends on the hippocampus. In Experiment 1, we investigated hippocampal contributions to within-domain STM-LTM integration by testing whether immediate verbal recall of words improves in MTL amnesic patients when words are presented in familiar verbal contexts (meaningful sentences) compared to unfamiliar verbal contexts (random word lists). Patients demonstrated a robust sentence superiority effect, whereby verbal STM performance improved in familiar compared to unfamiliar verbal contexts, and the magnitude of this effect did not differ from that in controls. In Experiment 2, we investigated hippocampal contributions to between-domain STM-LTM integration by testing whether immediate verbal recall of digits improves in MTL amnesic patients when digits are presented in a familiar visuospatial context (a typical keypad layout) compared to an unfamiliar visuospatial context (a random keypad layout). Immediate verbal recall improved in both patients and controls when digits were presented in the familiar compared to the unfamiliar keypad array, indicating a preserved ability to integrate activated verbal information with stored visuospatial knowledge. Together, these results demonstrate that immediate verbal recall in amnesia can benefit from two distinct types of semantic support, verbal and visuospatial, and that the hippocampus is not critical for leveraging stored semantic knowledge to improve memory performance. Copyright © 2015 Elsevier Ltd. All rights reserved.
Memory integration in amnesia: Prior knowledge supports verbal short-term memory
Race, Elizabeth; Palombo, Daniela J.; Cadden, Margaret; Burke, Keely; Verfaellie, Mieke
2015-01-01
Short-term memory (STM) and long-term memory (LTM) have traditionally been considered cognitively distinct. However, it is known that STM can improve when to-be-remembered information appears in contexts that make contact with prior knowledge, suggesting a more interactive relationship between STM and LTM. The current study investigated whether the ability to leverage LTM in support of STM critically depends on the integrity of the hippocampus. Specifically, we investigated whether the hippocampus differentially supports between-domain versus within-domain STM–LTM integration given prior evidence that the representational domain of the elements being integrated in memory is a critical determinant of whether memory performance depends on the hippocampus. In Experiment 1, we investigated hippocampal contributions to within-domain STM–LTM integration by testing whether immediate verbal recall of words improves in MTL amnesic patients when words are presented in familiar verbal contexts (meaningful sentences) compared to unfamiliar verbal contexts (random word lists). Patients demonstrated a robust sentence superiority effect, whereby verbal STM performance improved in familiar compared to unfamiliar verbal contexts, and the magnitude of this effect did not differ from that in controls. In Experiment 2, we investigated hippocampal contributions to between-domain STM–LTM integration by testing whether immediate verbal recall of digits improves in MTL amnesic patients when digits are presented in a familiar visuospatial context (a typical keypad layout) compared to an unfamiliar visuospatial context (a random keypad layout). Immediate verbal recall improved in both patients and controls when digits were presented in the familiar compared to the unfamiliar keypad array, indicating a preserved ability to integrate activated verbal information with stored visuospatial knowledge. Together, these results demonstrate that immediate verbal recall in amnesia can benefit from two distinct types of semantic support, verbal and visuospatial, and that the hippocampus is not critical for leveraging stored semantic knowledge to improve memory performance. PMID:25752585
Haslam, Catherine; Jetten, Jolanda; Haslam, S Alexander; Pugliese, Cara; Tonks, James
2011-05-01
The present research explores the relationship between the two components of autobiographical memory--episodic and semantic self-knowledge--and identity strength in older adults living in the community and residential care. Participants (N= 32) completed the autobiographical memory interview and measures of personal identity strength and multiple group memberships. Contrary to previous research, autobiographical memory for all time periods (childhood, early adulthood, and recent life) in the semantic domain was associated with greater strength in personal identity. Further, we obtained support for the hypothesis that the relationship between episodic self-knowledge and identity strength would be mediated by knowledge of personal semantic facts. However, there was also support for a reverse mediation model indicating that a strong sense of identity is associated with semantic self-knowledge and through this may enhance self-relevant recollection. The discussion elaborates on these findings and we propose a self-knowledge and identity model (SKIM) whereby semantic self-knowledge mediates a bidirectional relationship between episodic self-knowledge and identity. ©2010 The British Psychological Society.
Semantic Knowledge for Famous Names in Mild Cognitive Impairment
Seidenberg, Michael; Guidotti, Leslie; Nielson, Kristy A.; Woodard, John L.; Durgerian, Sally; Zhang, Qi; Gander, Amelia; Antuono, Piero; Rao, Stephen M.
2008-01-01
Person identification represents a unique category of semantic knowledge that is commonly impaired in Alzheimer's Disease (AD), but has received relatively little investigation in patients with Mild Cognitive Impairment (MCI). The current study examined the retrieval of semantic knowledge for famous names from three time epochs (recent, remote, and enduring) in two participant groups; 23 aMCI patients and 23 healthy elderly controls. The aMCI group was less accurate and produced less semantic knowledge than controls for famous names. Names from the enduring period were recognized faster than both recent and remote names in both groups, and remote names were recognized more quickly than recent names. Episodic memory performance was correlated with greater semantic knowledge particularly for recent names. We suggest that the anterograde memory deficits in the aMCI group interferes with learning of recent famous names and as a result produces difficulties with updating and integrating new semantic information with previously stored information. The implications of these findings for characterizing semantic memory deficits in MCI are discussed. PMID:19128524
ERIC Educational Resources Information Center
Ebbels, Susan H.; Nicoll, Hilary; Clark, Becky; Eachus, Beth; Gallagher, Aoife L.; Horniman, Karen; Jennings, Mary; McEvoy, Kate; Nimmo, Liz; Turner, Gail
2012-01-01
Background: Word-finding difficulties (WFDs) in children have been hypothesized to be caused at least partly by poor semantic knowledge. Therefore, improving semantic knowledge should decrease word-finding errors. Previous studies of semantic therapy for WFDs are inconclusive. Aims: To investigate the effectiveness of semantic therapy for…
Towards Semantic e-Science for Traditional Chinese Medicine
Chen, Huajun; Mao, Yuxin; Zheng, Xiaoqing; Cui, Meng; Feng, Yi; Deng, Shuiguang; Yin, Aining; Zhou, Chunying; Tang, Jinming; Jiang, Xiaohong; Wu, Zhaohui
2007-01-01
Background Recent advances in Web and information technologies with the increasing decentralization of organizational structures have resulted in massive amounts of information resources and domain-specific services in Traditional Chinese Medicine. The massive volume and diversity of information and services available have made it difficult to achieve seamless and interoperable e-Science for knowledge-intensive disciplines like TCM. Therefore, information integration and service coordination are two major challenges in e-Science for TCM. We still lack sophisticated approaches to integrate scientific data and services for TCM e-Science. Results We present a comprehensive approach to build dynamic and extendable e-Science applications for knowledge-intensive disciplines like TCM based on semantic and knowledge-based techniques. The semantic e-Science infrastructure for TCM supports large-scale database integration and service coordination in a virtual organization. We use domain ontologies to integrate TCM database resources and services in a semantic cyberspace and deliver a semantically superior experience including browsing, searching, querying and knowledge discovering to users. We have developed a collection of semantic-based toolkits to facilitate TCM scientists and researchers in information sharing and collaborative research. Conclusion Semantic and knowledge-based techniques are suitable to knowledge-intensive disciplines like TCM. It's possible to build on-demand e-Science system for TCM based on existing semantic and knowledge-based techniques. The presented approach in the paper integrates heterogeneous distributed TCM databases and services, and provides scientists with semantically superior experience to support collaborative research in TCM discipline. PMID:17493289
2017-01-01
Statistical approaches to emergent knowledge have tended to focus on the process by which experience of individual episodes accumulates into generalizable experience across episodes. However, there is a seemingly opposite, but equally critical, process that such experience affords: the process by which, from a space of types (e.g. onions—a semantic class that develops through exposure to individual episodes involving individual onions), we can perceive or create, on-the-fly, a specific token (a specific onion, perhaps one that is chopped) in the absence of any prior perceptual experience with that specific token. This article reviews a selection of statistical learning studies that lead to the speculation that this process—the generation, on the basis of semantic memory, of a novel episodic representation—is itself an instance of a statistical, in fact associative, process. The article concludes that the same processes that enable statistical abstraction across individual episodes to form semantic memories also enable the generation, from those semantic memories, of representations that correspond to individual tokens, and of novel episodic facts about those tokens. Statistical learning is a window onto these deeper processes that underpin cognition. This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences’. PMID:27872378
Altmann, Gerry T M
2017-01-05
Statistical approaches to emergent knowledge have tended to focus on the process by which experience of individual episodes accumulates into generalizable experience across episodes. However, there is a seemingly opposite, but equally critical, process that such experience affords: the process by which, from a space of types (e.g. onions-a semantic class that develops through exposure to individual episodes involving individual onions), we can perceive or create, on-the-fly, a specific token (a specific onion, perhaps one that is chopped) in the absence of any prior perceptual experience with that specific token. This article reviews a selection of statistical learning studies that lead to the speculation that this process-the generation, on the basis of semantic memory, of a novel episodic representation-is itself an instance of a statistical, in fact associative, process. The article concludes that the same processes that enable statistical abstraction across individual episodes to form semantic memories also enable the generation, from those semantic memories, of representations that correspond to individual tokens, and of novel episodic facts about those tokens. Statistical learning is a window onto these deeper processes that underpin cognition.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Author(s).
Making Semantic Waves: A Key to Cumulative Knowledge-Building
ERIC Educational Resources Information Center
Maton, Karl
2013-01-01
The paper begins by arguing that knowledge-blindness in educational research represents a serious obstacle to understanding knowledge-building. It then offers sociological concepts from Legitimation Code Theory--"semantic gravity" and "semantic density"--that systematically conceptualize one set of organizing principles underlying knowledge…
Action representation: crosstalk between semantics and pragmatics.
Prinz, Wolfgang
2014-03-01
Marc Jeannerod pioneered a representational approach to movement and action. In his approach, motor representations provide both, declarative knowledge about action and procedural knowledge for action (action semantics and action pragmatics, respectively). Recent evidence from language comprehension and action simulation supports the claim that action pragmatics and action semantics draw on common representational resources, thus challenging the traditional divide between declarative and procedural action knowledge. To account for these observations, three kinds of theoretical frameworks are discussed: (i) semantics is grounded in pragmatics, (ii) pragmatics is anchored in semantics, and (iii) pragmatics is part and parcel of semantics. © 2013 Elsevier Ltd. All rights reserved.
Haslam, Catherine; Sabah, Mazen
2013-03-01
The double dissociation involving person-specific and general semantic knowledge is supported by numerous patient studies, though cases with preservation of the former are few. In this paper, we report longitudinal data from two cases. Their knowledge in both domains was preserved at the start of the investigation, but progressive deterioration was primarily observed on tests of general semantics. These data strengthen the evidence-base for preservation of person-specific knowledge in semantic memory disorder, and support its separate representation from object knowledge. © 2012 The British Psychological Society.
Lyons, Frances; Kay, Janice; Hanley, J Richard; Haslam, Catherine
2006-01-01
A number of single cases in the literature demonstrate that person-specific semantic knowledge can be selectively impaired after acquired brain damage compared with that of object categories. However, there has been little unequivocal evidence for the reverse dissociation, selective preservation of person-specific semantic knowledge. Recently, three case studies have been published which provide support for the claim that such knowledge can be selectively preserved [Kay, J., & Hanley, J. R. (2002). Preservation of memory for people in semantic memory disorder: Further category-specific semantic dissociation. Cognitive Neuropsychology, 19, 113-134; Lyons, F., Hanley, J. R., & Kay, J. (2002). Anomia for common names and geographical names with preserved retrieval of names of people: A semantic memory disorder. Cortex, 38, 23-35; Thompson, S. A, Graham, K. S., Williams, G., Patterson, K., Kapur, N., & Hodges, J. R. (2004). Dissociating person-specific from general semantic knowledge: Roles of the left and right temporal lobes. Neuropsychologia, 42, 359-370]. In this paper, we supply further evidence from a series of 18 patients with acquired language disorder. Of this set, a number were observed to be impaired on tests of semantic association and word-picture matching using names of object categories (e.g. objects, animals and foods), but preserved on similar tests using names of famous people. Careful methodology was applied to match object and person-specific categories for item difficulty. The study also examined whether preservation of person-specific semantic knowledge was associated with preservation of knowledge of 'biological categories' such as fruit and vegetables and animals, or with preservation of 'token' knowledge of singular categories such as countries. The findings are discussed in the context of a variety of accounts that examine whether semantic memory has a categorical structure.
Knowledge represented using RDF semantic network in the concept of semantic web
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lukasova, A., E-mail: alena.lukasova@osu.cz; Vajgl, M., E-mail: marek.vajgl@osu.cz; Zacek, M., E-mail: martin.zacek@osu.cz
The RDF(S) model has been declared as the basic model to capture knowledge of the semantic web. It provides a common and flexible way to decompose composed knowledge to elementary statements, which can be represented by RDF triples or by RDF graph vectors. From the logical point of view, elements of knowledge can be expressed using at most binary predicates, which can be converted to RDF-triples or graph vectors. However, it is not able to capture implicit knowledge representable by logical formulas. This contribution shows how existing approaches (semantic networks and clausal form logic) can be combined together with RDFmore » to obtain RDF-compatible system with ability to represent implicit knowledge and inference over knowledge base.« less
Semantic-episodic interactions in the neuropsychology of disbelief.
Ladowsky-Brooks, Ricki; Alcock, James E
2007-03-01
The purpose of this paper is to outline ways in which characteristics of memory functioning determine truth judgements regarding verbally transmitted information. Findings on belief formation from several areas of psychology were reviewed in order to identify general principles that appear to underlie the designation of information in memory as "true" or "false". Studies on belief formation have demonstrated that individuals have a tendency to encode information as "true" and that an additional encoding step is required to tag information as "false". This additional step can involve acquisition and later recall of semantic-episodic associations between message content and contextual cues that signal that information is "false". Semantic-episodic interactions also appear to prevent new information from being accepted as "true" through encoding bias or the assignment of a "false" tag to data that is incompatible with prior knowledge. It is proposed that truth judgements are made through a combined weighting of the reliability of the information source and the compatibility of this information with already stored data. This requires interactions in memory. Failure to integrate different types of memories, such as semantic and episodic memories, can arise from mild hippocampal dysfunction and might result in delusions.
Grilli, Matthew D; Bercel, John J; Wank, Aubrey A; Rapcsak, Steven Z
2018-06-04
Autobiographical facts and personal trait knowledge are conceptualized as distinct types of personal semantics, but the cognitive and neural mechanisms that separate them remain underspecified. One distinction may be their level of specificity, with autobiographical facts reflecting idiosyncratic conceptual knowledge and personal traits representing basic level category knowledge about the self. Given the critical role of the left anterior ventrolateral temporal lobe (AVTL) in the storage and retrieval of semantic information about unique entities, we hypothesized that knowledge of autobiographical facts may depend on the integrity of this region to a greater extent than personal traits. To provide neuropsychological evidence relevant to this issue, we investigated personal semantics, semantic knowledge of non-personal unique entities, and episodic memory in two individuals with well-defined left (MK) versus right (DW) AVTL lesions. Relative to controls, MK demonstrated preserved personal trait knowledge but impaired "experience-far" (i.e., spatiotemporal independent) autobiographical fact knowledge, semantic memory for non-personal unique entities, and episodic memory. In contrast, both experience-far autobiographical facts and personal traits were spared in DW, whereas episodic memory and aspects of semantic memory for non-personal unique entities were impaired. These findings support the notion that autobiographical facts and personal traits have distinct cognitive features and neural mechanisms. They also suggest a common organizing principle for personal and non-personal semantics, namely the specificity of such knowledge to an entity, which is reflected in the contribution of the left AVTL to retrieval. Copyright © 2018 Elsevier Ltd. All rights reserved.
Semantic Categorization: A Comparison between Deaf and Hearing Children
ERIC Educational Resources Information Center
Ormel, Ellen A.; Gijsel, Martine A. R.; Hermans, Daan; Bosman, Anna M. T.; Knoors, Harry; Verhoeven, Ludo
2010-01-01
Learning to read is a major obstacle for children who are deaf. The otherwise significant role of phonology is often limited as a result of hearing loss. However, semantic knowledge may facilitate reading comprehension. One important aspect of semantic knowledge concerns semantic categorization. In the present study, the quality of the semantic…
Beal-Alvarez, Jennifer S; Figueroa, Daileen M
2017-04-01
Two key areas of language development include semantic and phonological knowledge. Semantic knowledge relates to word and concept knowledge. Phonological knowledge relates to how language parameters combine to create meaning. We investigated signing deaf adults' and children's semantic and phonological sign generation via one-minute tasks, including animals, foods, and specific handshapes. We investigated the effects of chronological age, age of sign language acquisition/years at school site, gender, presence of a disability, and geographical location (i.e., USA and Puerto Rico) on participants' performance and relations among tasks. In general, the phonological task appeared more difficult than the semantic tasks, students generated more animals than foods, age, and semantic performance correlated for the larger sample of U.S. students, and geographical variation included use of fingerspelling and specific signs. Compared to their peers, deaf students with disabilities generated fewer semantic items. These results provide an initial snapshot of students' semantic and phonological sign generation. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
The Role of Simple Semantics in the Process of Artificial Grammar Learning
ERIC Educational Resources Information Center
Öttl, Birgit; Jäger, Gerhard; Kaup, Barbara
2017-01-01
This study investigated the effect of semantic information on artificial grammar learning (AGL). Recursive grammars of different complexity levels (regular language, mirror language, copy language) were investigated in a series of AGL experiments. In the with-semantics condition, participants acquired semantic information prior to the AGL…
Semantics driven approach for knowledge acquisition from EMRs.
Perera, Sujan; Henson, Cory; Thirunarayan, Krishnaprasad; Sheth, Amit; Nair, Suhas
2014-03-01
Semantic computing technologies have matured to be applicable to many critical domains such as national security, life sciences, and health care. However, the key to their success is the availability of a rich domain knowledge base. The creation and refinement of domain knowledge bases pose difficult challenges. The existing knowledge bases in the health care domain are rich in taxonomic relationships, but they lack nontaxonomic (domain) relationships. In this paper, we describe a semiautomatic technique for enriching existing domain knowledge bases with causal relationships gleaned from Electronic Medical Records (EMR) data. We determine missing causal relationships between domain concepts by validating domain knowledge against EMR data sources and leveraging semantic-based techniques to derive plausible relationships that can rectify knowledge gaps. Our evaluation demonstrates that semantic techniques can be employed to improve the efficiency of knowledge acquisition.
Semantic Priming Revisited: In Search of Structural Age Change in Semantic Knowledge.
ERIC Educational Resources Information Center
Mergler, Nancy L.; And Others
Contradictory previous research results showing that (1) language knowledge does not decrease with age; and (2) age differences exist in semantic strategies for memory recall provide the impetus for a study of semantic priming in young adults (mean age = 20) and older adults (mean age = 70) by providing target and prime words with six different…
Péron, Julie A.; Piolino, Pascale; Moal-Boursiquot, Sandrine Le; Biseul, Isabelle; Leray, Emmanuelle; Bon, Laetitia; Desgranges, Béatrice; Eustache, Francis; Belliard, Serge
2015-01-01
Semantic dementia patients seem to have better knowledge of information linked to the self. More specifically, despite having severe semantic impairment, these patients show that they have more general information about the people they know personally by direct experience than they do about other individuals they know indirectly. However, the role of direct personal experience remains debated because of confounding factors such as frequency, recency of exposure, and affective relevance. We performed an exploratory study comparing the performance of five semantic dementia patients with that of 10 matched healthy controls on the recognition (familiarity judgment) and identification (biographic information recall) of personally familiar names vs. famous names. As expected, intergroup comparisons indicated a semantic breakdown in semantic dementia patients as compared with healthy controls. Moreover, unlike healthy controls, the semantic dementia patients recognized and identified personally familiar names better than they did famous names. This pattern of results suggests that direct personal experience indeed plays a specific role in the relative preservation of person-specific semantic meaning in semantic dementia. We discuss the role of direct personal experience on the preservation of semantic knowledge and the potential neurophysiological mechanisms underlying these processes. PMID:26635578
Enhancing acronym/abbreviation knowledge bases with semantic information.
Torii, Manabu; Liu, Hongfang
2007-10-11
In the biomedical domain, a terminology knowledge base that associates acronyms/abbreviations (denoted as SFs) with the definitions (denoted as LFs) is highly needed. For the construction such terminology knowledge base, we investigate the feasibility to build a system automatically assigning semantic categories to LFs extracted from text. Given a collection of pairs (SF,LF) derived from text, we i) assess the coverage of LFs and pairs (SF,LF) in the UMLS and justify the need of a semantic category assignment system; and ii) automatically derive name phrases annotated with semantic category and construct a system using machine learning. Utilizing ADAM, an existing collection of (SF,LF) pairs extracted from MEDLINE, our system achieved an f-measure of 87% when assigning eight UMLS-based semantic groups to LFs. The system has been incorporated into a web interface which integrates SF knowledge from multiple SF knowledge bases. Web site: http://gauss.dbb.georgetown.edu/liblab/SFThesurus.
The impact of impaired semantic knowledge on spontaneous iconic gesture production
Cocks, Naomi; Dipper, Lucy; Pritchard, Madeleine; Morgan, Gary
2013-01-01
Background Previous research has found that people with aphasia produce more spontaneous iconic gesture than control participants, especially during word-finding difficulties. There is some evidence that impaired semantic knowledge impacts on the diversity of gestural handshapes, as well as the frequency of gesture production. However, no previous research has explored how impaired semantic knowledge impacts on the frequency and type of iconic gestures produced during fluent speech compared with those produced during word-finding difficulties. Aims To explore the impact of impaired semantic knowledge on the frequency and type of iconic gestures produced during fluent speech and those produced during word-finding difficulties. Methods & Procedures A group of 29 participants with aphasia and 29 control participants were video recorded describing a cartoon they had just watched. All iconic gestures were tagged and coded as either “manner,” “path only,” “shape outline” or “other”. These gestures were then separated into either those occurring during fluent speech or those occurring during a word-finding difficulty. The relationships between semantic knowledge and gesture frequency and form were then investigated in the two different conditions. Outcomes & Results As expected, the participants with aphasia produced a higher frequency of iconic gestures than the control participants, but when the iconic gestures produced during word-finding difficulties were removed from the analysis, the frequency of iconic gesture was not significantly different between the groups. While there was not a significant relationship between the frequency of iconic gestures produced during fluent speech and semantic knowledge, there was a significant positive correlation between semantic knowledge and the proportion of word-finding difficulties that contained gesture. There was also a significant positive correlation between the speakers' semantic knowledge and the proportion of gestures that were produced during fluent speech that were classified as “manner”. Finally while not significant, there was a positive trend between semantic knowledge of objects and the production of “shape outline” gestures during word-finding difficulties for objects. Conclusions The results indicate that impaired semantic knowledge in aphasia impacts on both the iconic gestures produced during fluent speech and those produced during word-finding difficulties but in different ways. These results shed new light on the relationship between impaired language and iconic co-speech gesture production and also suggest that analysis of iconic gesture may be a useful addition to clinical assessment. PMID:24058228
Improving semantic scene understanding using prior information
NASA Astrophysics Data System (ADS)
Laddha, Ankit; Hebert, Martial
2016-05-01
Perception for ground robot mobility requires automatic generation of descriptions of the robot's surroundings from sensor input (cameras, LADARs, etc.). Effective techniques for scene understanding have been developed, but they are generally purely bottom-up in that they rely entirely on classifying features from the input data based on learned models. In fact, perception systems for ground robots have a lot of information at their disposal from knowledge about the domain and the task. For example, a robot in urban environments might have access to approximate maps that can guide the scene interpretation process. In this paper, we explore practical ways to combine such prior information with state of the art scene understanding approaches.
Learning to segment mouse embryo cells
NASA Astrophysics Data System (ADS)
León, Juan; Pardo, Alejandro; Arbeláez, Pablo
2017-11-01
Recent advances in microscopy enable the capture of temporal sequences during cell development stages. However, the study of such sequences is a complex task and time consuming task. In this paper we propose an automatic strategy to adders the problem of semantic and instance segmentation of mouse embryos using NYU's Mouse Embryo Tracking Database. We obtain our instance proposals as refined predictions from the generalized hough transform, using prior knowledge of the embryo's locations and their current cell stage. We use two main approaches to learn the priors: Hand crafted features and automatic learned features. Our strategy increases the baseline jaccard index from 0.12 up to 0.24 using hand crafted features and 0.28 by using automatic learned ones.
Lin, Nan; Guo, Qihao; Han, Zaizhu; Bi, Yanchao
2011-11-01
Neuropsychological and neuroimaging studies have indicated that motor knowledge is one potential dimension along which concepts are organized. Here we present further direct evidence for the effects of motor knowledge in accounting for categorical patterns across object domains (living vs. nonliving) and grammatical domains (nouns vs. verbs), as well as the integrity of other modality-specific knowledge (e.g., visual). We present a Chinese case, XRK, who suffered from semantic dementia with left temporal lobe atrophy. In naming and comprehension tasks, he performed better at nonliving items than at living items, and better at verbs than at nouns. Critically, multiple regression method revealed that these two categorical effects could be both accounted for by the charade rating, a continuous measurement of the significance of motor knowledge for a concept or a semantic feature. Furthermore, charade rating also predicted his performances on the generation frequency of semantic features of various modalities. These findings consolidate the significance of motor knowledge in conceptual organization and further highlights the interactions between different types of semantic knowledge. Copyright © 2010 Elsevier Inc. All rights reserved.
Montembeault, M; Brambati, S M; Joubert, S; Boukadi, M; Chapleau, M; Laforce, R Jr; Wilson, M A; Macoir, J; Rouleau, I
2017-01-27
While the semantic variant of primary progressive aphasia (svPPA) is characterized by a predominant semantic memory impairment, episodic memory impairments are the clinical hallmark of Alzheimer's disease (AD). However, AD patients also present with semantic deficits, which are more severe for semantically unique entities (e.g. a famous person) than for common concepts (e.g. a beaver). Previous studies in these patient populations have largely focused on famous-person naming. Therefore, we aimed to evaluate if these impairments also extend to other semantically unique entities such as famous places and famous logos. In this study, 13 AD patients, 9 svPPA patients, and 12 cognitively unimpaired elderly subjects (CTRL) were tested with a picture-naming test of non-unique entities (Boston Naming Test) and three experimental tests of semantically unique entities assessing naming of famous persons, places, and logos. Both clinical groups were overall more impaired at naming semantically unique entities than non-unique entities. Naming impairments in AD and svPPA extended to the other types of semantically unique entities, since a CTRL>AD>svPPA pattern was found on the performance of all naming tests. Naming famous places and famous persons appeared to be most impaired in svPPA, and both specific and general semantic knowledge for these entities were affected in these patients. Although AD patients were most significantly impaired on famous-person naming, only their specific semantic knowledge was impaired, while general knowledge was preserved. Post-hoc neuroimaging analyses also showed that famous-person naming impairments in AD correlated with atrophy in the temporo-parietal junction, a region functionally associated with lexical access. In line with previous studies, svPPA patients' impairment in both naming and semantic knowledge suggest a more profound semantic impairment, while naming impairments in AD may arise to a greater extent from impaired lexical access, even though semantic impairment for specific knowledge is also present. These results highlight the critical importance of developing and using a variety of semantically-unique-entity naming tests in neuropsychological assessments of patients with neurodegenerative diseases, which may unveil different patterns of lexical-semantic deficits. Copyright © 2016 Elsevier Ltd. All rights reserved.
Semantics of the visual environment encoded in parahippocampal cortex
Bonner, Michael F.; Price, Amy Rose; Peelle, Jonathan E.; Grossman, Murray
2016-01-01
Semantic representations capture the statistics of experience and store this information in memory. A fundamental component of this memory system is knowledge of the visual environment, including knowledge of objects and their associations. Visual semantic information underlies a range of behaviors, from perceptual categorization to cognitive processes such as language and reasoning. Here we examine the neuroanatomic system that encodes visual semantics. Across three experiments, we found converging evidence indicating that knowledge of verbally mediated visual concepts relies on information encoded in a region of the ventral-medial temporal lobe centered on parahippocampal cortex. In an fMRI study, this region was strongly engaged by the processing of concepts relying on visual knowledge but not by concepts relying on other sensory modalities. In a study of patients with the semantic variant of primary progressive aphasia (semantic dementia), atrophy that encompassed this region was associated with a specific impairment in verbally mediated visual semantic knowledge. Finally, in a structural study of healthy adults from the fMRI experiment, gray matter density in this region related to individual variability in the processing of visual concepts. The anatomic location of these findings aligns with recent work linking the ventral-medial temporal lobe with high-level visual representation, contextual associations, and reasoning through imagination. Together this work suggests a critical role for parahippocampal cortex in linking the visual environment with knowledge systems in the human brain. PMID:26679216
Semantics of the Visual Environment Encoded in Parahippocampal Cortex.
Bonner, Michael F; Price, Amy Rose; Peelle, Jonathan E; Grossman, Murray
2016-03-01
Semantic representations capture the statistics of experience and store this information in memory. A fundamental component of this memory system is knowledge of the visual environment, including knowledge of objects and their associations. Visual semantic information underlies a range of behaviors, from perceptual categorization to cognitive processes such as language and reasoning. Here we examine the neuroanatomic system that encodes visual semantics. Across three experiments, we found converging evidence indicating that knowledge of verbally mediated visual concepts relies on information encoded in a region of the ventral-medial temporal lobe centered on parahippocampal cortex. In an fMRI study, this region was strongly engaged by the processing of concepts relying on visual knowledge but not by concepts relying on other sensory modalities. In a study of patients with the semantic variant of primary progressive aphasia (semantic dementia), atrophy that encompassed this region was associated with a specific impairment in verbally mediated visual semantic knowledge. Finally, in a structural study of healthy adults from the fMRI experiment, gray matter density in this region related to individual variability in the processing of visual concepts. The anatomic location of these findings aligns with recent work linking the ventral-medial temporal lobe with high-level visual representation, contextual associations, and reasoning through imagination. Together, this work suggests a critical role for parahippocampal cortex in linking the visual environment with knowledge systems in the human brain.
Seek and you shall remember: Scene semantics interact with visual search to build better memories
Draschkow, Dejan; Wolfe, Jeremy M.; Võ, Melissa L.-H.
2014-01-01
Memorizing critical objects and their locations is an essential part of everyday life. In the present study, incidental encoding of objects in naturalistic scenes during search was compared to explicit memorization of those scenes. To investigate if prior knowledge of scene structure influences these two types of encoding differently, we used meaningless arrays of objects as well as objects in real-world, semantically meaningful images. Surprisingly, when participants were asked to recall scenes, their memory performance was markedly better for searched objects than for objects they had explicitly tried to memorize, even though participants in the search condition were not explicitly asked to memorize objects. This finding held true even when objects were observed for an equal amount of time in both conditions. Critically, the recall benefit for searched over memorized objects in scenes was eliminated when objects were presented on uniform, non-scene backgrounds rather than in a full scene context. Thus, scene semantics not only help us search for objects in naturalistic scenes, but appear to produce a representation that supports our memory for those objects beyond intentional memorization. PMID:25015385
English semantic word-pair norms and a searchable Web portal for experimental stimulus creation.
Buchanan, Erin M; Holmes, Jessica L; Teasley, Marilee L; Hutchison, Keith A
2013-09-01
As researchers explore the complexity of memory and language hierarchies, the need to expand normed stimulus databases is growing. Therefore, we present 1,808 words, paired with their features and concept-concept information, that were collected using previously established norming methods (McRae, Cree, Seidenberg, & McNorgan Behavior Research Methods 37:547-559, 2005). This database supplements existing stimuli and complements the Semantic Priming Project (Hutchison, Balota, Cortese, Neely, Niemeyer, Bengson, & Cohen-Shikora 2010). The data set includes many types of words (including nouns, verbs, adjectives, etc.), expanding on previous collections of nouns and verbs (Vinson & Vigliocco Journal of Neurolinguistics 15:317-351, 2008). We describe the relation between our and other semantic norms, as well as giving a short review of word-pair norms. The stimuli are provided in conjunction with a searchable Web portal that allows researchers to create a set of experimental stimuli without prior programming knowledge. When researchers use this new database in tandem with previous norming efforts, precise stimuli sets can be created for future research endeavors.
Kuperberg, Gina R; Delaney-Busch, Nathaniel; Fanucci, Kristina; Blackford, Trevor
2018-01-01
Lexico-semantic disturbances are considered central to schizophrenia. Clinically, their clearest manifestation is in language production. However, most studies probing their underlying mechanisms have used comprehension or categorization tasks. Here, we probed automatic semantic activity prior to language production in schizophrenia using event-related potentials (ERPs). 19 people with schizophrenia and 16 demographically-matched healthy controls named target pictures that were very quickly preceded by masked prime words. To probe automatic semantic activity prior to production, we measured the N400 ERP component evoked by these targets. To determine the origin of any automatic semantic abnormalities, we manipulated the type of relationship between prime and target such that they overlapped in (a) their semantic features (semantically related, e.g. "cake" preceding a < picture of a pie >, (b) their initial phonemes (phonemically related, e.g. "stomach" preceding a < picture of a starfish >), or (c) both their semantic features and their orthographic/phonological word form (identity related, e.g. "socks" preceding a < picture of socks >). For each of these three types of relationship, the same targets were paired with unrelated prime words (counterbalanced across lists). We contrasted ERPs and naming times to each type of related target with its corresponding unrelated target. People with schizophrenia showed abnormal N400 modulation prior to naming identity related (versus unrelated) targets: whereas healthy control participants produced a smaller amplitude N400 to identity related than unrelated targets, patients showed the opposite pattern, producing a larger N400 to identity related than unrelated targets. This abnormality was specific to the identity related targets. Just like healthy control participants, people with schizophrenia produced a smaller N400 to semantically related than to unrelated targets, and showed no difference in the N400 evoked by phonemically related and unrelated targets. There were no differences between the two groups in the pattern of naming times across conditions. People with schizophrenia can show abnormal neural activity associated with automatic semantic processing prior to language production. The specificity of this abnormality to the identity related targets suggests that that, rather than arising from abnormalities of either semantic features or lexical form alone, it may stem from disruptions of mappings (connections) between the meaning of words and their form.
A Model for New Linkages for Prior Learning Assessment
ERIC Educational Resources Information Center
Kalz, Marco; van Bruggen, Jan; Giesbers, Bas; Waterink, Wim; Eshuis, Jannes; Koper, Rob
2008-01-01
Purpose: The purpose of this paper is twofold: first the paper aims to sketch the theoretical basis for the use of electronic portfolios for prior learning assessment; second it endeavours to introduce latent semantic analysis (LSA) as a powerful method for the computation of semantic similarity between texts and a basis for a new observation link…
Knowledge-Based Topic Model for Unsupervised Object Discovery and Localization.
Niu, Zhenxing; Hua, Gang; Wang, Le; Gao, Xinbo
Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object instances from a given image collection without any supervision. Previous work has attempted to tackle this problem with vanilla topic models, such as latent Dirichlet allocation (LDA). However, in those methods no prior knowledge for the given image collection is exploited to facilitate object discovery. On the other hand, the topic models used in those methods suffer from the topic coherence issue-some inferred topics do not have clear meaning, which limits the final performance of object discovery. In this paper, prior knowledge in terms of the so-called must-links are exploited from Web images on the Internet. Furthermore, a novel knowledge-based topic model, called LDA with mixture of Dirichlet trees, is proposed to incorporate the must-links into topic modeling for object discovery. In particular, to better deal with the polysemy phenomenon of visual words, the must-link is re-defined as that one must-link only constrains one or some topic(s) instead of all topics, which leads to significantly improved topic coherence. Moreover, the must-links are built and grouped with respect to specific object classes, thus the must-links in our approach are semantic-specific , which allows to more efficiently exploit discriminative prior knowledge from Web images. Extensive experiments validated the efficiency of our proposed approach on several data sets. It is shown that our method significantly improves topic coherence and outperforms the unsupervised methods for object discovery and localization. In addition, compared with discriminative methods, the naturally existing object classes in the given image collection can be subtly discovered, which makes our approach well suited for realistic applications of unsupervised object discovery.Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object instances from a given image collection without any supervision. Previous work has attempted to tackle this problem with vanilla topic models, such as latent Dirichlet allocation (LDA). However, in those methods no prior knowledge for the given image collection is exploited to facilitate object discovery. On the other hand, the topic models used in those methods suffer from the topic coherence issue-some inferred topics do not have clear meaning, which limits the final performance of object discovery. In this paper, prior knowledge in terms of the so-called must-links are exploited from Web images on the Internet. Furthermore, a novel knowledge-based topic model, called LDA with mixture of Dirichlet trees, is proposed to incorporate the must-links into topic modeling for object discovery. In particular, to better deal with the polysemy phenomenon of visual words, the must-link is re-defined as that one must-link only constrains one or some topic(s) instead of all topics, which leads to significantly improved topic coherence. Moreover, the must-links are built and grouped with respect to specific object classes, thus the must-links in our approach are semantic-specific , which allows to more efficiently exploit discriminative prior knowledge from Web images. Extensive experiments validated the efficiency of our proposed approach on several data sets. It is shown that our method significantly improves topic coherence and outperforms the unsupervised methods for object discovery and localization. In addition, compared with discriminative methods, the naturally existing object classes in the given image collection can be subtly discovered, which makes our approach well suited for realistic applications of unsupervised object discovery.
The Role of Context in Remembering Familiar Persons: Insights from Semantic Dementia
ERIC Educational Resources Information Center
Joubert, Sven; Mauries, Sandrine; Barbeau, Emmanuel; Ceccaldi, Mathieu; Poncet, Michel
2004-01-01
Semantic dementia (SD) is a progressive condition characterized by an insidious and gradual breakdown in semantic knowledge. Patients suffering from this condition gradually lose their knowledge of objects and their attributes, concepts, famous persons, and public events. In contrast, these patients maintain a striking preservation of…
ERIC Educational Resources Information Center
Mason-Baughman, Mary Beth; Wallace, Sarah E.
2014-01-01
Previous studies suggest that people with aphasia have incomplete lexical-semantic representations with decreased low-importance distinctive (LID) feature knowledge. In addition, decreased LID feature knowledge correlates with ability to discriminate among semantically related words. The current study seeks to replicate and extend previous…
The representation of semantic knowledge in a child with Williams syndrome.
Robinson, Sally J; Temple, Christine M
2009-05-01
This study investigated whether there are distinct types of semantic knowledge with distinct representational bases during development. The representation of semantic knowledge in a teenage child (S.T.) with Williams syndrome was explored for the categories of animals, fruit, and vegetables, manipulable objects, and nonmanipulable objects. S.T.'s lexical stores were of a normal size but the volume of "sensory feature" semantic knowledge she generated in oral descriptions was reduced. In visual recognition decisions, S.T. made more false positives to nonitems than did controls. Although overall naming of pictures was unimpaired, S.T. exhibited a category-specific anomia for nonmanipulable objects and impaired naming of visual-feature descriptions of animals. S.T.'s performance was interpreted as reflecting the impaired integration of distinctive features from perceptual input, which may impact upon nonmanipulable objects to a greater extent than the other knowledge categories. Performance was used to inform adult-based models of semantic representation, with category structure proposed to emerge due to differing degrees of dependency upon underlying knowledge types, feature correlations, and the acquisition of information from modality-specific processing modules.
ERIC Educational Resources Information Center
Paczynski, Martin; Kuperberg, Gina R.
2012-01-01
We aimed to determine whether semantic relatedness between an incoming word and its preceding context can override expectations based on two types of stored knowledge: real-world knowledge about the specific events and states conveyed by a verb, and the verb's broader selection restrictions on the animacy of its argument. We recorded event-related…
Semantic Analysis of Email Using Domain Ontologies and WordNet
NASA Technical Reports Server (NTRS)
Berrios, Daniel C.; Keller, Richard M.
2005-01-01
The problem of capturing and accessing knowledge in paper form has been supplanted by a problem of providing structure to vast amounts of electronic information. Systems that can construct semantic links for natural language documents like email messages automatically will be a crucial element of semantic email tools. We have designed an information extraction process that can leverage the knowledge already contained in an existing semantic web, recognizing references in email to existing nodes in a network of ontology instances by using linguistic knowledge and knowledge of the structure of the semantic web. We developed a heuristic score that uses several forms of evidence to detect references in email to existing nodes in the Semanticorganizer repository's network. While these scores cannot directly support automated probabilistic inference, they can be used to rank nodes by relevance and link those deemed most relevant to email messages.
Biran, Michal; Friedmann, Naama
2012-10-01
This study explored lexical-syntactic information - syntactic information that is stored in the lexicon - and its relation to syntactic and lexical impairments in aphasia. We focused on two types of lexical-syntactic information: predicate argument structure (PAS) of verbs (the number and types of arguments the verb selects) and grammatical gender of nouns. The participants were 17 Hebrew-speaking individuals with aphasia who had a syntactic deficit (agrammatism) or a lexical retrieval deficit (anomia) located at the semantic lexicon, the phonological output lexicon, or the phonological output buffer. After testing the participants' syntactic and lexical retrieval abilities and establishing the functional loci of their deficits, we assessed their PAS and grammatical gender knowledge. This assessment included sentence completion, sentence production, sentence repetition, and grammaticality judgment tasks. The participants' performance on these tests yielded several important dissociations. Three agrammatic participants had impaired syntax but unimpaired PAS knowledge. Three agrammatic participants had impaired syntax but unimpaired grammatical gender knowledge. This indicates that lexical-syntactic information is represented separately from syntax, and can be spared even when syntax at the sentence level, such as embedding and movement are impaired. All 5 individuals with phonological output buffer impairment and all 3 individuals with phonological output lexicon impairment had preserved lexical-syntactic knowledge. These selective impairments indicate that lexical-syntactic information is represented at a lexical stage prior to the phonological lexicon and the phonological buffer. Three participants with impaired PAS (aPASia) and impaired grammatical gender who showed intact lexical-semantic knowledge indicate that the lexical-syntactic information is represented separately from the semantic lexicon. This led us to conclude that lexical-syntactic information is stored in a separate syntactic lexicon. A double dissociation between PAS and grammatical gender impairments indicated that different types of lexical-syntactic information are represented separately in this syntactic lexicon. Copyright © 2011 Elsevier Srl. All rights reserved.
Long-Term Semantic Priming of Word Meaning
ERIC Educational Resources Information Center
Woltz, Dan J.
2010-01-01
Three experiments investigated facilitation in synonym decisions as a function of prior synonym decision trials that were either identical or semantically related. Experiment 1 demonstrated that semantically related prime trials produced less facilitation than identical prime trials, but facilitation from both persisted over 14 intervening trials.…
Inborn and experience-dependent models of categorical brain organization. A position paper
Gainotti, Guido
2015-01-01
The present review aims to summarize the debate in contemporary neuroscience between inborn and experience-dependent models of conceptual representations that goes back to the description of category-specific semantic disorders for biological and artifact categories. Experience-dependent models suggest that categorical disorders are the by-product of the differential weighting of different sources of knowledge in the representation of biological and artifact categories. These models maintain that semantic disorders are not really category-specific, because they do not respect the boundaries between different categories. They also argue that the brain structures which are disrupted in a given type of category-specific semantic disorder should correspond to the areas of convergence of the sensory-motor information which play a major role in the construction of that category. Furthermore, they provide a simple interpretation of gender-related categorical effects and are supported by studies assessing the importance of prior experience in the cortical representation of objects On the other hand, inborn models maintain that category-specific semantic disorders reflect the disruption of innate brain networks, which are shaped by natural selection to allow rapid identification of objects that are very relevant for survival. From the empirical point of view, these models are mainly supported by observations of blind subjects, which suggest that visual experience is not necessary for the emergence of category-specificity in the ventral stream of visual processing. The weight of the data supporting experience-dependent and inborn models is thoroughly discussed, stressing the fact observations made in blind subjects are still the subject of intense debate. It is concluded that at the present state of knowledge it is not possible to choose between experience-dependent and inborn models of conceptual representations. PMID:25667570
The benefits of sensorimotor knowledge: body-object interaction facilitates semantic processing.
Siakaluk, Paul D; Pexman, Penny M; Sears, Christopher R; Wilson, Kim; Locheed, Keri; Owen, William J
2008-04-05
This article examined the effects of body-object interaction (BOI) on semantic processing. BOI measures perceptions of the ease with which a human body can physically interact with a word's referent. In Experiment 1, BOI effects were examined in 2 semantic categorization tasks (SCT) in which participants decided if words are easily imageable. Responses were faster and more accurate for high BOI words (e.g., mask) than for low BOI words (e.g., ship). In Experiment 2, BOI effects were examined in a semantic lexical decision task (SLDT), which taps both semantic feedback and semantic processing. The BOI effect was larger in the SLDT than in the SCT, suggesting that BOI facilitates both semantic feedback and semantic processing. The findings are consistent with the embodied cognition perspective (e.g., Barsalou's, 1999, Perceptual Symbols Theory), which proposes that sensorimotor interactions with the environment are incorporated in semantic knowledge. 2008 Cognitive Science Society, Inc.
NASA Astrophysics Data System (ADS)
Laird, John E.
2009-05-01
Our long-term goal is to develop autonomous robotic systems that have the cognitive abilities of humans, including communication, coordination, adapting to novel situations, and learning through experience. Our approach rests on the recent integration of the Soar cognitive architecture with both virtual and physical robotic systems. Soar has been used to develop a wide variety of knowledge-rich agents for complex virtual environments, including distributed training environments and interactive computer games. For development and testing in robotic virtual environments, Soar interfaces to a variety of robotic simulators and a simple mobile robot. We have recently made significant extensions to Soar that add new memories and new non-symbolic reasoning to Soar's original symbolic processing, which should significantly improve Soar abilities for control of robots. These extensions include episodic memory, semantic memory, reinforcement learning, and mental imagery. Episodic memory and semantic memory support the learning and recalling of prior events and situations as well as facts about the world. Reinforcement learning provides the ability of the system to tune its procedural knowledge - knowledge about how to do things. Mental imagery supports the use of diagrammatic and visual representations that are critical to support spatial reasoning. We speculate on the future of unmanned systems and the need for cognitive robotics to support dynamic instruction and taskability.
Semantic Knowledge Use in Discourse: Influence of Age
ERIC Educational Resources Information Center
Kintz, Stephen; Wright, Heather Harris
2017-01-01
Semantic memory is relatively stable across the lifespan (LaBarge, Edwards, & Knesevich, 1986). However, most research has been conducted at the single concept level (LaBarge et al., 1986, Spaniol et al., 2006). Few researchers have examined how semantic knowledge is used in discourse. The purpose of the study, then, was to determine the…
Practical Experiences for the Development of Educational Systems in the Semantic Web
ERIC Educational Resources Information Center
Sánchez Vera, Ma. del Mar; Tomás Fernández Breis, Jesualdo; Serrano Sánchez, José Luis; Prendes Espinosa, Ma. Paz
2013-01-01
Semantic Web technologies have been applied in educational settings for different purposes in recent years, with the type of application being mainly defined by the way in which knowledge is represented and exploited. The basic technology for knowledge representation in Semantic Web settings is the ontology, which represents a common, shareable…
Semantic Similarity of Labels and Inductive Generalization: Taking a Second Look
ERIC Educational Resources Information Center
Fisher, Anna V.; Matlen, Bryan J.; Godwin, Karrie E.
2011-01-01
Prior research suggests that preschoolers can generalize object properties based on category information conveyed by semantically-similar labels. However, previous research did not control for co-occurrence probability of labels in natural speech. The current studies re-assessed children's generalization with semantically-similar labels.…
Semantic Processing of Previews within Compound Words
ERIC Educational Resources Information Center
White, Sarah J.; Bertram, Raymond; Hyona, Jukka
2008-01-01
Previous studies have suggested that previews of words prior to fixation can be processed orthographically, but not semantically, during reading of sentences (K. Rayner, D. A. Balota, & A. Pollatsek, 1986). The present study tested whether semantic processing of previews can occur within words. The preview of the second constituent of…
Semantic computing and language knowledge bases
NASA Astrophysics Data System (ADS)
Wang, Lei; Wang, Houfeng; Yu, Shiwen
2017-09-01
As the proposition of the next-generation Web - semantic Web, semantic computing has been drawing more and more attention within the circle and the industries. A lot of research has been conducted on the theory and methodology of the subject, and potential applications have also been investigated and proposed in many fields. The progress of semantic computing made so far cannot be detached from its supporting pivot - language resources, for instance, language knowledge bases. This paper proposes three perspectives of semantic computing from a macro view and describes the current status of affairs about the construction of language knowledge bases and the related research and applications that have been carried out on the basis of these resources via a case study in the Institute of Computational Linguistics at Peking University.
Computer assessment of interview data using latent semantic analysis.
Dam, Gregory; Kaufmann, Stefan
2008-02-01
Clinical interviews are a powerful method for assessing students' knowledge and conceptualdevelopment. However, the analysis of the resulting data is time-consuming and can create a "bottleneck" in large-scale studies. This article demonstrates the utility of computational methods in supporting such an analysis. Thirty-four 7th-grade student explanations of the causes of Earth's seasons were assessed using latent semantic analysis (LSA). Analyses were performed on transcriptions of student responses during interviews administered, prior to (n = 21) and after (n = 13) receiving earth science instruction. An instrument that uses LSA technology was developed to identify misconceptions and assess conceptual change in students' thinking. Its accuracy, as determined by comparing its classifications to the independent coding performed by four human raters, reached 90%. Techniques for adapting LSA technology to support the analysis of interview data, as well as some limitations, are discussed.
The trajectory of scientific discovery: concept co-occurrence and converging semantic distance.
Cohen, Trevor; Schvaneveldt, Roger W
2010-01-01
The paradigm of literature-based knowledge discovery originated by Swanson involves finding meaningful associations between terms or concepts that have not occurred together in any previously published document. While several automated approaches have been applied to this problem, these generally evaluate the literature at a point in time, and do not evaluate the role of change over time in distributional statistics as an indicator of meaningful implicit associations. To address this issue, we develop and evaluate Symmetric Random Indexing (SRI), a novel variant of the Random Indexing (RI) approach that is able to measure implicit association over time. SRI is found to compare favorably to existing RI variants in the prediction of future direct co-occurrence. Summary statistics over several experiments suggest a trend of converging semantic distance prior to the co-occurrence of key terms for two seminal historical literature-based discoveries.
Personal semantics: at the crossroads of semantic and episodic memory.
Renoult, Louis; Davidson, Patrick S R; Palombo, Daniela J; Moscovitch, Morris; Levine, Brian
2012-11-01
Declarative memory is usually described as consisting of two systems: semantic and episodic memory. Between these two poles, however, may lie a third entity: personal semantics (PS). PS concerns knowledge of one's past. Although typically assumed to be an aspect of semantic memory, it is essentially absent from existing models of knowledge. Furthermore, like episodic memory (EM), PS is idiosyncratically personal (i.e., not culturally-shared). We show that, depending on how it is operationalized, the neural correlates of PS can look more similar to semantic memory, more similar to EM, or dissimilar to both. We consider three different perspectives to better integrate PS into existing models of declarative memory and suggest experimental strategies for disentangling PS from semantic and episodic memory. Copyright © 2012 Elsevier Ltd. All rights reserved.
Informatics in radiology: radiology gamuts ontology: differential diagnosis for the Semantic Web.
Budovec, Joseph J; Lam, Cesar A; Kahn, Charles E
2014-01-01
The Semantic Web is an effort to add semantics, or "meaning," to empower automated searching and processing of Web-based information. The overarching goal of the Semantic Web is to enable users to more easily find, share, and combine information. Critical to this vision are knowledge models called ontologies, which define a set of concepts and formalize the relations between them. Ontologies have been developed to manage and exploit the large and rapidly growing volume of information in biomedical domains. In diagnostic radiology, lists of differential diagnoses of imaging observations, called gamuts, provide an important source of knowledge. The Radiology Gamuts Ontology (RGO) is a formal knowledge model of differential diagnoses in radiology that includes 1674 differential diagnoses, 19,017 terms, and 52,976 links between terms. Its knowledge is used to provide an interactive, freely available online reference of radiology gamuts ( www.gamuts.net ). A Web service allows its content to be discovered and consumed by other information systems. The RGO integrates radiologic knowledge with other biomedical ontologies as part of the Semantic Web. © RSNA, 2014.
A Graph-Based Recovery and Decomposition of Swanson’s Hypothesis using Semantic Predications
Cameron, Delroy; Bodenreider, Olivier; Yalamanchili, Hima; Danh, Tu; Vallabhaneni, Sreeram; Thirunarayan, Krishnaprasad; Sheth, Amit P.; Rindflesch, Thomas C.
2014-01-01
Objectives This paper presents a methodology for recovering and decomposing Swanson’s Raynaud Syndrome–Fish Oil Hypothesis semi-automatically. The methodology leverages the semantics of assertions extracted from biomedical literature (called semantic predications) along with structured background knowledge and graph-based algorithms to semi-automatically capture the informative associations originally discovered manually by Swanson. Demonstrating that Swanson’s manually intensive techniques can be undertaken semi-automatically, paves the way for fully automatic semantics-based hypothesis generation from scientific literature. Methods Semantic predications obtained from biomedical literature allow the construction of labeled directed graphs which contain various associations among concepts from the literature. By aggregating such associations into informative subgraphs, some of the relevant details originally articulated by Swanson has been uncovered. However, by leveraging background knowledge to bridge important knowledge gaps in the literature, a methodology for semi-automatically capturing the detailed associations originally explicated in natural language by Swanson has been developed. Results Our methodology not only recovered the 3 associations commonly recognized as Swanson’s Hypothesis, but also decomposed them into an additional 16 detailed associations, formulated as chains of semantic predications. Altogether, 14 out of the 19 associations that can be attributed to Swanson were retrieved using our approach. To the best of our knowledge, such an in-depth recovery and decomposition of Swanson’s Hypothesis has never been attempted. Conclusion In this work therefore, we presented a methodology for semi- automatically recovering and decomposing Swanson’s RS-DFO Hypothesis using semantic representations and graph algorithms. Our methodology provides new insights into potential prerequisites for semantics-driven Literature-Based Discovery (LBD). These suggest that three critical aspects of LBD include: 1) the need for more expressive representations beyond Swanson’s ABC model; 2) an ability to accurately extract semantic information from text; and 3) the semantic integration of scientific literature with structured background knowledge. PMID:23026233
ERIC Educational Resources Information Center
Haebig, Eileen; Kaushanskaya, Margarita; Weismer, Susan Ellis
2015-01-01
Children with autism spectrum disorder (ASD) and specific language impairment (SLI) often have immature lexical-semantic knowledge; however, the organization of lexical-semantic knowledge is poorly understood. This study examined lexical processing in school-age children with ASD, SLI, and typical development, who were matched on receptive…
ERIC Educational Resources Information Center
Li, Yanyan; Dong, Mingkai; Huang, Ronghuai
2011-01-01
The knowledge society requires life-long learning and flexible learning environment that enables fast, just-in-time and relevant learning, aiding the development of communities of knowledge, linking learners and practitioners with experts. Based upon semantic wiki, a combination of wiki and Semantic Web technology, this paper designs and develops…
Semantic Document Model to Enhance Data and Knowledge Interoperability
NASA Astrophysics Data System (ADS)
Nešić, Saša
To enable document data and knowledge to be efficiently shared and reused across application, enterprise, and community boundaries, desktop documents should be completely open and queryable resources, whose data and knowledge are represented in a form understandable to both humans and machines. At the same time, these are the requirements that desktop documents need to satisfy in order to contribute to the visions of the Semantic Web. With the aim of achieving this goal, we have developed the Semantic Document Model (SDM), which turns desktop documents into Semantic Documents as uniquely identified and semantically annotated composite resources, that can be instantiated into human-readable (HR) and machine-processable (MP) forms. In this paper, we present the SDM along with an RDF and ontology-based solution for the MP document instance. Moreover, on top of the proposed model, we have built the Semantic Document Management System (SDMS), which provides a set of services that exploit the model. As an application example that takes advantage of SDMS services, we have extended MS Office with a set of tools that enables users to transform MS Office documents (e.g., MS Word and MS PowerPoint) into Semantic Documents, and to search local and distant semantic document repositories for document content units (CUs) over Semantic Web protocols.
Macoir, Joël; Berubé-Lalancette, Sarah; Wilson, Maximiliano A; Laforce, Robert; Hudon, Carol; Gravel, Pierre; Potvin, Olivier; Duchesne, Simon; Monetta, Laura
2016-12-01
Music can induce particular emotions and activate semantic knowledge. In the semantic variant of primary progressive aphasia (svPPA), semantic memory is impaired as a result of anterior temporal lobe (ATL) atrophy. Semantics is responsible for the encoding and retrieval of factual knowledge about music, including associative and emotional attributes. In the present study, we report the performance of two individuals with svPPA in three experiments. NG with bilateral ATL atrophy and ND with atrophy largely restricted to the left ATL. Experiment 1 assessed the recognition of musical excerpts and both patients were unimpaired. Experiment 2 studied the emotions conveyed by music and only NG showed impaired performance. Experiment 3 tested the association of semantic concepts to musical excerpts and both patients were impaired. These results suggest that the right ATL seems essential for the recognition of emotions conveyed by music and that the left ATL is involved in binding music to semantics. They are in line with the notion that the ATLs are devoted to the binding of different modality-specific properties and suggest that they are also differentially involved in the processing of factual and emotional knowledge associated with music.
McGregor, Karla K.; Oleson, Jacob
2017-01-01
Purpose The purpose of this study is to determine whether deficits in executive function and lexical-semantic memory compromise the linguistic performance of young adults with specific learning disabilities (LD) enrolled in postsecondary studies. Method One hundred eighty-five students with LD (n = 53) or normal language development (ND, n = 132) named items in the categories animals and food for 1 minute for each category and completed tests of lexical-semantic knowledge and executive control of memory. Groups were compared on total names, mean cluster size, frequency of embedded clusters, frequency of cluster switches, and change in fluency over time. Secondary analyses of variability within the LD group were also conducted. Results The LD group was less fluent than the ND group. Within the LD group, lexical-semantic knowledge predicted semantic fluency and cluster size; executive control of memory predicted semantic fluency and cluster switches. The LD group produced smaller clusters and fewer embedded clusters than the ND group. Groups did not differ in switching or change over time. Conclusions Deficits in the lexical-semantic system associated with LD may persist into young adulthood, even among those who have managed their disability well enough to attend college. Lexical-semantic deficits are associated with compromised semantic fluency, and the two problems are more likely among students with more severe disabilities. PMID:28267833
Hall, Jessica; McGregor, Karla K; Oleson, Jacob
2017-03-01
The purpose of this study is to determine whether deficits in executive function and lexical-semantic memory compromise the linguistic performance of young adults with specific learning disabilities (LD) enrolled in postsecondary studies. One hundred eighty-five students with LD (n = 53) or normal language development (ND, n = 132) named items in the categories animals and food for 1 minute for each category and completed tests of lexical-semantic knowledge and executive control of memory. Groups were compared on total names, mean cluster size, frequency of embedded clusters, frequency of cluster switches, and change in fluency over time. Secondary analyses of variability within the LD group were also conducted. The LD group was less fluent than the ND group. Within the LD group, lexical-semantic knowledge predicted semantic fluency and cluster size; executive control of memory predicted semantic fluency and cluster switches. The LD group produced smaller clusters and fewer embedded clusters than the ND group. Groups did not differ in switching or change over time. Deficits in the lexical-semantic system associated with LD may persist into young adulthood, even among those who have managed their disability well enough to attend college. Lexical-semantic deficits are associated with compromised semantic fluency, and the two problems are more likely among students with more severe disabilities.
Abstract knowledge versus direct experience in processing of binomial expressions
Morgan, Emily; Levy, Roger
2016-01-01
We ask whether word order preferences for binomial expressions of the form A and B (e.g. bread and butter) are driven by abstract linguistic knowledge of ordering constraints referencing the semantic, phonological, and lexical properties of the constituent words, or by prior direct experience with the specific items in questions. Using forced-choice and self-paced reading tasks, we demonstrate that online processing of never-before-seen binomials is influenced by abstract knowledge of ordering constraints, which we estimate with a probabilistic model. In contrast, online processing of highly frequent binomials is primarily driven by direct experience, which we estimate from corpus frequency counts. We propose a trade-off wherein processing of novel expressions relies upon abstract knowledge, while reliance upon direct experience increases with increased exposure to an expression. Our findings support theories of language processing in which both compositional generation and direct, holistic reuse of multi-word expressions play crucial roles. PMID:27776281
Lehrner, J; Coutinho, G; Mattos, P; Moser, D; Pflüger, M; Gleiss, A; Auff, E; Dal-Bianco, P; Pusswald, G; Stögmann, E
2017-07-01
Semantic memory may be impaired in clinically recognized states of cognitive impairment. We investigated the relationship between semantic memory and depressive symptoms (DS) in patients with cognitive impairment. 323 cognitively healthy controls and 848 patients with subjective cognitive decline (SCD), mild cognitive impairment (MCI), and Alzheimer's disease (AD) dementia were included. Semantic knowledge for famous faces, world capitals, and word vocabulary was investigated. Compared to healthy controls, we found a statistically significant difference of semantic knowledge in the MCI groups and the AD group, respectively. Results of the SCD group were mixed. However, two of the three semantic memory measures (world capitals and word vocabulary) showed a significant association with DS. We found a difference in semantic memory performance in MCI and AD as well as an association with DS. Results suggest that the difference in semantic memory is due to a storage loss rather than to a retrieval problem.
Semantic-syntactic partial word knowledge growth through reading.
Wagovich, Stacy A; Hill, Margaret S; Petroski, Gregory F
2015-02-01
Incidental reading provides a powerful opportunity for partial word knowledge growth in the school-age years. The extent to which children of differing language abilities can use reading experiences to glean partial knowledge of words is not well understood. The purpose of this study was to compare semantic-syntactic partial word knowledge growth of children with higher language skills (HL group; overall language standard scores of 85 or higher) to that of children with relatively lower language skills (LL group; overall receptive or expressive standard score below 85). Thirty-two children, 16 per group, silently read stories containing unfamiliar nouns and verbs 3 times over a 1-week period. Semantic-syntactic partial word knowledge growth was assessed after each reading and 2-3 days later to assess retention. Over time, both groups showed significant partial word knowledge growth, with the HL group showing significantly more growth. In addition, both groups retained knowledge several days later. Regardless of language skill level, children benefit from multiple exposures to unfamiliar words in reading in their development and retention of semantic-syntactic partial word knowledge growth.
ERIC Educational Resources Information Center
Hamada, Akira
2015-01-01
Three experiments examined whether the process of lexical inferences differs according to the direction of contextual elaboration using a semantic relatedness judgment task. In Experiment 1, Japanese university students read English sentences where target unknown words were semantically elaborated by prior contextual information (forward lexical…
Semantic Priming for Coordinate Distant Concepts in Alzheimer's Disease Patients
ERIC Educational Resources Information Center
Perri, R.; Zannino, G. D.; Caltagirone, C.; Carlesimo, G. A.
2011-01-01
Semantic priming paradigms have been used to investigate semantic knowledge in patients with Alzheimer's disease (AD). While priming effects produced by prime-target pairs with associative relatedness reflect processes at both lexical and semantic levels, priming effects produced by words that are semantically related but not associated should…
Individual Variability in the Semantic Processing of English Compound Words
ERIC Educational Resources Information Center
Schmidtke, Daniel; Van Dyke, Julie A.; Kuperman, Victor
2018-01-01
Semantic transparency effects during compound word recognition provide critical insight into the organization of semantic knowledge and the nature of semantic processing. The past 25 years of psycholinguistic research on compound semantic transparency has produced discrepant effects, leaving the existence and nature of its influence unresolved. In…
English Orthographic Learning in Chinese-L1 Young EFL Beginners.
Cheng, Yu-Lin
2017-12-01
English orthographic learning, among Chinese-L1 children who were beginning to learn English as a foreign language, was documented when: (1) only visual memory was at their disposal, (2) visual memory and either some letter-sound knowledge or some semantic information was available, and (3) visual memory, some letter-sound knowledge and some semantic information were all available. When only visual memory was available, orthographic learning (measured via an orthographic choice test) was meagre. Orthographic learning was significant when either semantic information or letter-sound knowledge supplemented visual memory, with letter-sound knowledge generating greater significance. Although the results suggest that letter-sound knowledge plays a more important role than semantic information, letter-sound knowledge alone does not suffice to achieve perfect orthographic learning, as orthographic learning was greatest when letter-sound knowledge and semantic information were both available. The present findings are congruent with a view that the orthography of a foreign language drives its orthographic learning more than L1 orthographic learning experience, thus extending Share's (Cognition 55:151-218, 1995) self-teaching hypothesis to include non-alphabetic L1 children's orthographic learning of an alphabetic foreign language. The little letter-sound knowledge development observed in the experiment-I control group indicates that very little letter-sound knowledge develops in the absence of dedicated letter-sound training. Given the important role of letter-sound knowledge in English orthographic learning, dedicated letter-sound instruction is highly recommended.
A Semantic Lexicon-Based Approach for Sense Disambiguation and Its WWW Application
NASA Astrophysics Data System (ADS)
di Lecce, Vincenzo; Calabrese, Marco; Soldo, Domenico
This work proposes a basic framework for resolving sense disambiguation through the use of Semantic Lexicon, a machine readable dictionary managing both word senses and lexico-semantic relations. More specifically, polysemous ambiguity characterizing Web documents is discussed. The adopted Semantic Lexicon is WordNet, a lexical knowledge-base of English words widely adopted in many research studies referring to knowledge discovery. The proposed approach extends recent works on knowledge discovery by focusing on the sense disambiguation aspect. By exploiting the structure of WordNet database, lexico-semantic features are used to resolve the inherent sense ambiguity of written text with particular reference to HTML resources. The obtained results may be extended to generic hypertextual repositories as well. Experiments show that polysemy reduction can be used to hint about the meaning of specific senses in given contexts.
ERIC Educational Resources Information Center
Deane, Paul; Lawless, René R.; Li, Chen; Sabatini, John; Bejar, Isaac I.; O'Reilly, Tenaha
2014-01-01
We expect that word knowledge accumulates gradually. This article draws on earlier approaches to assessing depth, but focuses on one dimension: richness of semantic knowledge. We present results from a study in which three distinct item types were developed at three levels of depth: knowledge of common usage patterns, knowledge of broad topical…
Research in Knowledge Representation for Natural Language Understanding
1980-11-01
artificial intelligence, natural language understanding , parsing, syntax, semantics, speaker meaning, knowledge representation, semantic networks...TinB PAGE map M W006 1Report No. 4513 L RESEARCH IN KNOWLEDGE REPRESENTATION FOR NATURAL LANGUAGE UNDERSTANDING Annual Report 1 September 1979 to 31... understanding , knowledge representation, and knowledge based inference. The work that we have been doing falls into three classes, successively motivated by
ERIC Educational Resources Information Center
Masullo, Carlo; Piccininni, Chiara; Quaranta, Davide; Vita, Maria Gabriella; Gaudino, Simona; Gainotti, Guido
2012-01-01
Semantic memory was investigated in a patient (MR) affected by a severe apperceptive visual agnosia, due to an ischemic cerebral lesion, bilaterally affecting the infero-mesial parts of the temporo-occipital cortices. The study was made by means of a Semantic Knowledge Questionnaire (Laiacona, Barbarotto, Trivelli, & Capitani, 1993), which takes…
Haebig, Eileen; Kaushanskaya, Margarita; Ellis Weismer, Susan
2015-12-01
Children with autism spectrum disorder (ASD) and specific language impairment (SLI) often have immature lexical-semantic knowledge; however, the organization of lexical-semantic knowledge is poorly understood. This study examined lexical processing in school-age children with ASD, SLI, and typical development, who were matched on receptive vocabulary. Children completed a lexical decision task, involving words with high and low semantic network sizes and nonwords. Children also completed nonverbal updating and shifting tasks. Children responded more accurately to words from high than from low semantic networks; however, follow-up analyses identified weaker semantic network effects in the SLI group. Additionally, updating and shifting abilities predicted lexical processing, demonstrating similarity in the mechanisms which underlie semantic processing in children with ASD, SLI, and typical development.
Haebig, Eileen; Kaushanskaya, Margarita; Weismer, Susan Ellis
2016-01-01
Children with autism spectrum disorder (ASD) and specific language impairment (SLI) often have immature lexical-semantic knowledge; however, the organization of lexical-semantic knowledge is poorly understood. This study examined lexical processing in school-age children with ASD, SLI, and typical development, who were matched on receptive vocabulary. Children completed a lexical decision task, involving words with high and low semantic network sizes and nonwords. Children also completed nonverbal updating and shifting tasks. Children responded more accurately to words from high than from low semantic networks; however, follow-up analyses identified weaker semantic network effects in the SLI group. Additionally, updating and shifting abilities predicted lexical processing, demonstrating similarity in the mechanisms which underlie semantic processing in children with ASD, SLI, and typical development. PMID:26210517
Comesaña, Montserrat; Soares, Ana Paula; Sánchez-Casas, Rosa; Lima, Cátia
2012-08-01
How bilinguals represent words in two languages and which mechanisms are responsible for second language acquisition are important questions in the bilingual and vocabulary acquisition literature. This study aims to analyse the effect of two learning methods (picture- vs. word-based method) and two types of words (cognates and non-cognates) in early stages of children's L2 acquisition. Forty-eight native speakers of European Portuguese, all sixth graders (mean age = 10.87 years; SD= 0.85), participated in the study. None of them had prior knowledge of Basque (the L2 in this study). After a learning phase in which L2 words were learned either by a picture- or a word-based method, children were tested in a backward-word translation recognition task at two times (immediately vs. one week later). Results showed that the participants made more errors when rejecting semantically related than semantically unrelated words as correct translations (semantic interference effect). The magnitude of this effect was higher in the delayed test condition regardless of the learning method. Moreover, the overall performance of participants from the word-based method was better than the performance of participants from the picture-word method. Results were discussed concerning the most significant bilingual lexical processing models. ©2011 The British Psychological Society.
Heterogeniety and Heterarchy: How far can network analyses in Earth and space sciences?
NASA Astrophysics Data System (ADS)
Prabhu, A.; Fox, P. A.; Eleish, A.; Li, C.; Pan, F.; Zhong, H.
2017-12-01
The vast majority of explorations of Earth systems are limited in their ability to effectively explore the most important (often most difficult) problems because they are forced to interconnect at the data-element, or syntactic, level rather than at a higher scientific, or conceptual/ semantic, level. Recent successes in the application of complex network theory and algorithms to minerology, fossils and proteins over billions of years of Earth's history, raise expectations that more general graph-based approaches offer the opportunity for new discoveries = needles instead of haystacks. In the past 10 years in the natural sciences there has substantial progress in providing both specialists and non-specialists the ability to describe in machine readable form, geophysical quantities and relations among them in meaningful and natural ways, effectively breaking the prior syntax barrier. The corresponding open-world semantics and reasoning provide higher-level interconnections. That is, semantics provided around the data structures, using open-source tools, allow for discovery at the knowledge level. This presentation will cover the fundamentals of data-rich network analyses for geosciences, provide illustrative examples in mineral evolution and offer future paths for consideration.
Falkman, Göran; Gustafsson, Marie; Jontell, Mats; Torgersson, Olof
2008-08-26
Information technology (IT) support for remote collaboration of geographically distributed communities of practice (CoP) in health care must deal with a number of sociotechnical aspects of communication within the community. In the mid-1990s, participants of the Swedish Oral Medicine Network (SOMNet) began discussing patient cases in telephone conferences. The cases were distributed prior to the conferences using PowerPoint and email. For the technical support of online CoP, Semantic Web technologies can potentially fulfill needs of knowledge reuse, data exchange, and reasoning based on ontologies. However, more research is needed on the use of Semantic Web technologies in practice. The objectives of this research were to (1) study the communication of distributed health care professionals in oral medicine; (2) apply Semantic Web technologies to describe community data and oral medicine knowledge; (3) develop an online CoP, Swedish Oral Medicine Web (SOMWeb), centered on user-contributed case descriptions and meetings; and (4) evaluate SOMWeb and study how work practices change with IT support. Based on Java, and using the Web Ontology Language and Resource Description Framework for handling community data and oral medicine knowledge, SOMWeb was developed using a user-centered and iterative approach. For studying the work practices and evaluating the system, a mixed-method approach of interviews, observations, and a questionnaire was used. By May 2008, there were 90 registered users of SOMWeb, 93 cases had been added, and 18 meetings had utilized the system. The introduction of SOMWeb has improved the structure of meetings and their discussions, and a tenfold increase in the number of participants has been observed. Users submit cases to seek advice on diagnosis or treatment, to show an unusual case, or to create discussion. Identified barriers to submitting cases are lack of time, concern about whether the case is interesting enough, and showing gaps in one's own knowledge. Three levels of member participation are discernable: a core group that contributes most cases and most meeting feedback; an active group that participates often but only sometimes contribute cases and feedback; and a large peripheral group that seldom or never contribute cases or feedback. SOMWeb is beneficial for individual clinicians as well as for the SOMNet community. The system provides an opportunity for its members to share both high quality clinical practice knowledge and external evidence related to complex oral medicine cases. The foundation in Semantic Web technologies enables formalization and structuring of case data that can be used for further reasoning and research. Main success factors are the long history of collaboration between different disciplines, the user-centered development approach, the existence of a "champion" within the field, and nontechnical community aspects already being in place.
Gustafsson, Marie; Jontell, Mats; Torgersson, Olof
2008-01-01
Background Information technology (IT) support for remote collaboration of geographically distributed communities of practice (CoP) in health care must deal with a number of sociotechnical aspects of communication within the community. In the mid-1990s, participants of the Swedish Oral Medicine Network (SOMNet) began discussing patient cases in telephone conferences. The cases were distributed prior to the conferences using PowerPoint and email. For the technical support of online CoP, Semantic Web technologies can potentially fulfill needs of knowledge reuse, data exchange, and reasoning based on ontologies. However, more research is needed on the use of Semantic Web technologies in practice. Objectives The objectives of this research were to (1) study the communication of distributed health care professionals in oral medicine; (2) apply Semantic Web technologies to describe community data and oral medicine knowledge; (3) develop an online CoP, Swedish Oral Medicine Web (SOMWeb), centered on user-contributed case descriptions and meetings; and (4) evaluate SOMWeb and study how work practices change with IT support. Methods Based on Java, and using the Web Ontology Language and Resource Description Framework for handling community data and oral medicine knowledge, SOMWeb was developed using a user-centered and iterative approach. For studying the work practices and evaluating the system, a mixed-method approach of interviews, observations, and a questionnaire was used. Results By May 2008, there were 90 registered users of SOMWeb, 93 cases had been added, and 18 meetings had utilized the system. The introduction of SOMWeb has improved the structure of meetings and their discussions, and a tenfold increase in the number of participants has been observed. Users submit cases to seek advice on diagnosis or treatment, to show an unusual case, or to create discussion. Identified barriers to submitting cases are lack of time, concern about whether the case is interesting enough, and showing gaps in one’s own knowledge. Three levels of member participation are discernable: a core group that contributes most cases and most meeting feedback; an active group that participates often but only sometimes contribute cases and feedback; and a large peripheral group that seldom or never contribute cases or feedback. Conclusions SOMWeb is beneficial for individual clinicians as well as for the SOMNet community. The system provides an opportunity for its members to share both high quality clinical practice knowledge and external evidence related to complex oral medicine cases. The foundation in Semantic Web technologies enables formalization and structuring of case data that can be used for further reasoning and research. Main success factors are the long history of collaboration between different disciplines, the user-centered development approach, the existence of a “champion” within the field, and nontechnical community aspects already being in place. PMID:18725355
The Role of Simple Semantics in the Process of Artificial Grammar Learning.
Öttl, Birgit; Jäger, Gerhard; Kaup, Barbara
2017-10-01
This study investigated the effect of semantic information on artificial grammar learning (AGL). Recursive grammars of different complexity levels (regular language, mirror language, copy language) were investigated in a series of AGL experiments. In the with-semantics condition, participants acquired semantic information prior to the AGL experiment; in the without-semantics control condition, participants did not receive semantic information. It was hypothesized that semantics would generally facilitate grammar acquisition and that the learning benefit in the with-semantics conditions would increase with increasing grammar complexity. Experiment 1 showed learning effects for all grammars but no performance difference between conditions. Experiment 2 replicated the absence of a semantic benefit for all grammars even though semantic information was more prominent during grammar acquisition as compared to Experiment 1. Thus, we did not find evidence for the idea that semantics facilitates grammar acquisition, which seems to support the view of an independent syntactic processing component.
The role of sleep spindles and slow-wave activity in integrating new information in semantic memory.
Tamminen, Jakke; Lambon Ralph, Matthew A; Lewis, Penelope A
2013-09-25
Assimilating new information into existing knowledge is a fundamental part of consolidating new memories and allowing them to guide behavior optimally and is vital for conceptual knowledge (semantic memory), which is accrued over many years. Sleep is important for memory consolidation, but its impact upon assimilation of new information into existing semantic knowledge has received minimal examination. Here, we examined the integration process by training human participants on novel words with meanings that fell into densely or sparsely populated areas of semantic memory in two separate sessions. Overnight sleep was polysomnographically monitored after each training session and recall was tested immediately after training, after a night of sleep, and 1 week later. Results showed that participants learned equal numbers of both word types, thus equating amount and difficulty of learning across the conditions. Measures of word recognition speed showed a disadvantage for novel words in dense semantic neighborhoods, presumably due to interference from many semantically related concepts, suggesting that the novel words had been successfully integrated into semantic memory. Most critically, semantic neighborhood density influenced sleep architecture, with participants exhibiting more sleep spindles and slow-wave activity after learning the sparse compared with the dense neighborhood words. These findings provide the first evidence that spindles and slow-wave activity mediate integration of new information into existing semantic networks.
Marques, J Frederico
2007-12-01
The deterioration of semantic memory usually proceeds from more specific to more general superordinate categories, although rarer cases of superordinate knowledge impairment have also been reported. The nature of superordinate knowledge and the explanation of these two semantic impairments were evaluated from the analysis of superordinate and basic-level feature norms. The results show that, in comparison to basic-level concepts, superordinate concepts are not generally less informative and have similar feature distinctiveness and proportion of individual sensory features, but their features are less shared by their members. Results are in accord with explanations based on feature connection weights and/or concept confusability for the superordinate advantage cases. Results especially support an explanation for superordinate impairments in terms of higher semantic control requirements as related to features being less shared between concept members. Implications for patients with semantic impairments are also discussed.
Brown, Thackery I; Rissman, Jesse; Chow, Tiffany E; Uncapher, Melina R; Wagner, Anthony D
2018-04-18
Autobiographical remembering can depend on two forms of memory: episodic (event) memory and autobiographical semantic memory (remembering personally relevant semantic knowledge, independent of recalling a specific experience). There is debate about the degree to which the neural signals that support episodic recollection relate to or build upon autobiographical semantic remembering. Pooling data from two fMRI studies of memory for real-world personal events, we investigated whether medial temporal lobe (MTL) and parietal subregions contribute to autobiographical episodic and semantic remembering. During scanning, participants made memory judgments about photograph sequences depicting past events from their life or from others' lives, and indicated whether memory was based on episodic or semantic knowledge. Results revealed several distinct functional patterns: activity in most MTL subregions was selectively associated with autobiographical episodic memory; the hippocampal tail, superior parietal lobule, and intraparietal sulcus were similarly engaged when memory was based on retrieval of an autobiographical episode or autobiographical semantic knowledge; and angular gyrus demonstrated a graded pattern, with activity declining from autobiographical recollection to autobiographical semantic remembering to correct rejections of novel events. Collectively, our data offer insights into MTL and parietal cortex functional organization, and elucidate circuitry that supports different forms of real-world autobiographical memory.
Towards semantic interoperability for electronic health records.
Garde, Sebastian; Knaup, Petra; Hovenga, Evelyn; Heard, Sam
2007-01-01
In the field of open electronic health records (EHRs), openEHR as an archetype-based approach is being increasingly recognised. It is the objective of this paper to shortly describe this approach, and to analyse how openEHR archetypes impact on health professionals and semantic interoperability. Analysis of current approaches to EHR systems, terminology and standards developments. In addition to literature reviews, we organised face-to-face and additional telephone interviews and tele-conferences with members of relevant organisations and committees. The openEHR archetypes approach enables syntactic interoperability and semantic interpretability -- both important prerequisites for semantic interoperability. Archetypes enable the formal definition of clinical content by clinicians. To enable comprehensive semantic interoperability, the development and maintenance of archetypes needs to be coordinated internationally and across health professions. Domain knowledge governance comprises a set of processes that enable the creation, development, organisation, sharing, dissemination, use and continuous maintenance of archetypes. It needs to be supported by information technology. To enable EHRs, semantic interoperability is essential. The openEHR archetypes approach enables syntactic interoperability and semantic interpretability. However, without coordinated archetype development and maintenance, 'rank growth' of archetypes would jeopardize semantic interoperability. We therefore believe that openEHR archetypes and domain knowledge governance together create the knowledge environment required to adopt EHRs.
Callahan, Brandy L; Joubert, Sven; Tremblay, Marie-Pier; Macoir, Joël; Belleville, Sylvie; Rousseau, François; Bouchard, Rémi W; Verret, Louis; Hudon, Carol
2015-06-01
Amnestic mild cognitive impairment (aMCI) and late-life depression (LLD) both increase the risk of developing Alzheimer disease (AD). Very little is known about the similarities and differences between these syndromes. The present study addresses this issue by examining the nature of semantic memory impairment (more precisely, object-based knowledge) in patients at risk of developing AD. Participants were 17 elderly patients with aMCI, 18 patients with aMCI plus depressive symptoms (aMCI/D+), 15 patients with LLD, and 29 healthy controls. All participants were aged 55 years or older and were administered a semantic battery designed to assess semantic knowledge for 16 biological and 16 man-made items. Overall performance of aMCI/D+ participants was significantly worse than the 3 other groups, and performance for questions assessing knowledge for biological items was poorer than for questions relating to man-made items. This study is the first to show that aMCI/D+ is associated with object-based semantic memory impairment. These results support the view that semantic deficits in aMCI are associated with concomitant depressive symptoms. However, depressive symptoms alone do not account exclusively for semantic impairment, since patients with LLD showed no semantic memory deficit. © The Author(s) 2014.
Rassinoux, A-M
2011-01-01
To summarize excellent current research in the field of knowledge representation and management (KRM). A synopsis of the articles selected for the IMIA Yearbook 2011 is provided and an attempt to highlight the current trends in the field is sketched. This last decade, with the extension of the text-based web towards a semantic-structured web, NLP techniques have experienced a renewed interest in knowledge extraction. This trend is corroborated through the five papers selected for the KRM section of the Yearbook 2011. They all depict outstanding studies that exploit NLP technologies whenever possible in order to accurately extract meaningful information from various biomedical textual sources. Bringing semantic structure to the meaningful content of textual web pages affords the user with cooperative sharing and intelligent finding of electronic data. As exemplified by the best paper selection, more and more advanced biomedical applications aim at exploiting the meaningful richness of free-text documents in order to generate semantic metadata and recently to learn and populate domain ontologies. These later are becoming a key piece as they allow portraying the semantics of the Semantic Web content. Maintaining their consistency with documents and semantic annotations that refer to them is a crucial challenge of the Semantic Web for the coming years.
A semantic web framework to integrate cancer omics data with biological knowledge.
Holford, Matthew E; McCusker, James P; Cheung, Kei-Hoi; Krauthammer, Michael
2012-01-25
The RDF triple provides a simple linguistic means of describing limitless types of information. Triples can be flexibly combined into a unified data source we call a semantic model. Semantic models open new possibilities for the integration of variegated biological data. We use Semantic Web technology to explicate high throughput clinical data in the context of fundamental biological knowledge. We have extended Corvus, a data warehouse which provides a uniform interface to various forms of Omics data, by providing a SPARQL endpoint. With the querying and reasoning tools made possible by the Semantic Web, we were able to explore quantitative semantic models retrieved from Corvus in the light of systematic biological knowledge. For this paper, we merged semantic models containing genomic, transcriptomic and epigenomic data from melanoma samples with two semantic models of functional data - one containing Gene Ontology (GO) data, the other, regulatory networks constructed from transcription factor binding information. These two semantic models were created in an ad hoc manner but support a common interface for integration with the quantitative semantic models. Such combined semantic models allow us to pose significant translational medicine questions. Here, we study the interplay between a cell's molecular state and its response to anti-cancer therapy by exploring the resistance of cancer cells to Decitabine, a demethylating agent. We were able to generate a testable hypothesis to explain how Decitabine fights cancer - namely, that it targets apoptosis-related gene promoters predominantly in Decitabine-sensitive cell lines, thus conveying its cytotoxic effect by activating the apoptosis pathway. Our research provides a framework whereby similar hypotheses can be developed easily.
Information Warfare: Evaluation of Operator Information Processing Models
1997-10-01
that people can describe or report, including both episodic and semantic information. Declarative memory contains a network of knowledge represented...second dimension corresponds roughly to the distinction between episodic and semantic memory that is commonly made in cognitive psychology. Episodic ...3 is long-term memory for the discourse, a subset of episodic memory . Partition 4 is long-term semantic memory , or the knowledge-base. According to
Rivasseau Jonveaux, T; Batt, M; Empereur, F; Braun, M; Trognon, A
2015-04-01
Episodic and semantic processes are involved in temporality used in daily life. Episodic memory permits one to place an event on the time axis, while semantic memory makes us aware of the time segmentation and its symbolic representation. Memory of the knowledge connected to the passing of time is materialized on the calendar and can be seen symbolically on the dial of a clock. In AD, semantic memory processes are preserved longer than processes related to episodic memory. We wonder whether the specific field of knowledge about time is altered during AD. We validated a specific evaluation with a control group (354 healthy subjects). Then we applied this battery to assess AD patients to appreciate the feasibility of this tool for this population. We then compared 22 AD patients with a control group matched for age, sex and educational level. Our clinical scale of temporal semantic knowledge consists of four parts: (a) hour reading with a.m. and p.m. hours; (b) using a clock: 12 clock faces with the hour numbers already placed: the patient draws hour and minute hands for various hours; (c) temporal segmentation: exploration of the knowledge on daytime scale and of the calendar; (d) time duration estimation: calculate how long the interview has lasted after indicating the time of its beginning and its end, then the time between 10.40 to 12.00. While age and educational level had an influence on all the scores, in the two groups control and patients, gender did not. Temporal segmentation, independent of the cultural level, revealed the best acquired knowledge in our control population. All the scores differentiated patients from control subjects. The temporal semantic knowledge correlated with the AD severity seemed to be correlated with the attention, verbal comprehension, and some components of executive functions, but was not related to the clock drawing test result. Depression did not have any influence on this scale in our AD group. The temporal semantic knowledge clinical scale shows differential alterations, notably in hour reading and using a clock, and less in temporal segmentation. Temporal semantic knowledge is altered in AD. The diagnosis and follow-up of these alterations allow professionals and caregivers to consider adaptations of the patient's environment according to their needs. Copyright © 2013 L’Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.
Musical and verbal semantic memory: two distinct neural networks?
Groussard, M; Viader, F; Hubert, V; Landeau, B; Abbas, A; Desgranges, B; Eustache, F; Platel, H
2010-02-01
Semantic memory has been investigated in numerous neuroimaging and clinical studies, most of which have used verbal or visual, but only very seldom, musical material. Clinical studies have suggested that there is a relative neural independence between verbal and musical semantic memory. In the present study, "musical semantic memory" is defined as memory for "well-known" melodies without any knowledge of the spatial or temporal circumstances of learning, while "verbal semantic memory" corresponds to general knowledge about concepts, again without any knowledge of the spatial or temporal circumstances of learning. Our aim was to compare the neural substrates of musical and verbal semantic memory by administering the same type of task in each modality. We used high-resolution PET H(2)O(15) to observe 11 young subjects performing two main tasks: (1) a musical semantic memory task, where the subjects heard the first part of familiar melodies and had to decide whether the second part they heard matched the first, and (2) a verbal semantic memory task with the same design, but where the material consisted of well-known expressions or proverbs. The musical semantic memory condition activated the superior temporal area and inferior and middle frontal areas in the left hemisphere and the inferior frontal area in the right hemisphere. The verbal semantic memory condition activated the middle temporal region in the left hemisphere and the cerebellum in the right hemisphere. We found that the verbal and musical semantic processes activated a common network extending throughout the left temporal neocortex. In addition, there was a material-dependent topographical preference within this network, with predominantly anterior activation during musical tasks and predominantly posterior activation during semantic verbal tasks. Copyright (c) 2009 Elsevier Inc. All rights reserved.
Gainotti, Guido
2011-04-01
In recent years, the anatomical and functional bases of conceptual activity have attracted a growing interest. In particular, Patterson and Lambon-Ralph have proposed the existence, in the anterior parts of the temporal lobes, of a mechanism (the 'amodal semantic hub') supporting the interactive activation of semantic representations in all modalities and for all semantic categories. The aim of then present paper is to discuss this model, arguing against the notion of an 'amodal' semantic hub, because we maintain, in agreement with the Damasio's construct of 'higher-order convergence zone', that a continuum exists between perceptual information and conceptual representations, whereas the 'amodal' account views perceptual informations only as a channel through which abstract semantic knowledge can be activated. According to our model, semantic organization can be better explained by two orthogonal higher-order convergence systems, concerning, on one hand, the right vs. left hemisphere and, on the other hand, the ventral vs. dorsal processing pathways. This model posits that conceptual representations may be mainly based upon perceptual activities in the right hemisphere and upon verbal mediation in the left side of the brain. It also assumes that conceptual knowledge based on the convergence of highly processed visual information with other perceptual data (and mainly concerning living categories) may be bilaterally represented in the anterior parts of the temporal lobes, whereas knowledge based on the integration of visual data with action schemata (namely knowledge of actions, body parts and artefacts) may be more represented in the left fronto-temporo-parietal areas. Copyright © 2010 Elsevier Inc. All rights reserved.
Altered brain response for semantic knowledge in Alzheimer's disease.
Wierenga, Christina E; Stricker, Nikki H; McCauley, Ashley; Simmons, Alan; Jak, Amy J; Chang, Yu-Ling; Nation, Daniel A; Bangen, Katherine J; Salmon, David P; Bondi, Mark W
2011-02-01
Word retrieval deficits are common in Alzheimer's disease (AD) and are thought to reflect a degradation of semantic memory. Yet, the nature of semantic deterioration in AD and the underlying neural correlates of these semantic memory changes remain largely unknown. We examined the semantic memory impairment in AD by investigating the neural correlates of category knowledge (e.g., living vs. nonliving) and featural processing (global vs. local visual information). During event-related fMRI, 10 adults diagnosed with mild AD and 22 cognitively normal (CN) older adults named aloud items from three categories for which processing of specific visual features has previously been dissociated from categorical features. Results showed widespread group differences in the categorical representation of semantic knowledge in several language-related brain areas. For example, the right inferior frontal gyrus showed selective brain response for nonliving items in the CN group but living items in the AD group. Additionally, the AD group showed increased brain response for word retrieval irrespective of category in Broca's homologue in the right hemisphere and rostral cingulate cortex bilaterally, which suggests greater recruitment of frontally mediated neural compensatory mechanisms in the face of semantic alteration. Copyright © 2010 Elsevier Ltd. All rights reserved.
Research in Knowledge Representation for Natural Language Understanding.
1984-09-01
TYPE OF REPORT & PERIOO COVERED RESEARCH IN KNOWLEDGE REPRESENTATION Annual Report FOR NATURAL LANGUAGE UNDERSTANDING 9/1/83 - 8/31/84 S. PERFORMING...nhaber) Artificial intelligence, natural language understanding , knowledge representation, semantics, semantic networks, KL-TWO, NIKL, belief and...attempting to understand and react to a complex, evolving situation. This report summarizes our research in knowledge representation and natural language
Huebner, Philip A.; Willits, Jon A.
2018-01-01
Previous research has suggested that distributional learning mechanisms may contribute to the acquisition of semantic knowledge. However, distributional learning mechanisms, statistical learning, and contemporary “deep learning” approaches have been criticized for being incapable of learning the kind of abstract and structured knowledge that many think is required for acquisition of semantic knowledge. In this paper, we show that recurrent neural networks, trained on noisy naturalistic speech to children, do in fact learn what appears to be abstract and structured knowledge. We trained two types of recurrent neural networks (Simple Recurrent Network, and Long Short-Term Memory) to predict word sequences in a 5-million-word corpus of speech directed to children ages 0–3 years old, and assessed what semantic knowledge they acquired. We found that learned internal representations are encoding various abstract grammatical and semantic features that are useful for predicting word sequences. Assessing the organization of semantic knowledge in terms of the similarity structure, we found evidence of emergent categorical and hierarchical structure in both models. We found that the Long Short-term Memory (LSTM) and SRN are both learning very similar kinds of representations, but the LSTM achieved higher levels of performance on a quantitative evaluation. We also trained a non-recurrent neural network, Skip-gram, on the same input to compare our results to the state-of-the-art in machine learning. We found that Skip-gram achieves relatively similar performance to the LSTM, but is representing words more in terms of thematic compared to taxonomic relations, and we provide reasons why this might be the case. Our findings show that a learning system that derives abstract, distributed representations for the purpose of predicting sequential dependencies in naturalistic language may provide insight into emergence of many properties of the developing semantic system. PMID:29520243
Electrophysiological evidence for effects of color knowledge in object recognition.
Lu, Aitao; Xu, Guiping; Jin, Hua; Mo, Lei; Zhang, Jijia; Zhang, John X
2010-01-29
Knowledge about the typical colors associated with familiar everyday objects (i.e., strawberries are red) is well-known to be represented in the conceptual semantic system. Evidence that such knowledge may also play a role in early perceptual processes for object recognition is scant. In the present ERP study, participants viewed a list of object pictures and detected infrequent stimulus repetitions. Results show that shortly after stimulus onset, ERP components indexing early perceptual processes, including N1, P2, and N2, differentiated between objects in their appropriate or congruent color from these objects in an inappropriate or incongruent color. Such congruence effect also occurred in N3 associated with semantic processing of pictures but not in N4 for domain-general semantic processing. Our results demonstrate a clear effect of color knowledge in early object recognition stages and support the following proposal-color as a surface property is stored in a multiple-memory system where pre-semantic perceptual and semantic conceptual representations interact during object recognition. (c) 2009 Elsevier Ireland Ltd. All rights reserved.
[Does action semantic knowledge influence mental simulation in sentence comprehension?].
Mochizuki, Masaya; Naito, Katsuo
2012-04-01
This research investigated whether action semantic knowledge influences mental simulation during sentence comprehension. In Experiment 1, we confirmed that the words of face-related objects include the perceptual knowledge about the actions that bring the object to the face. In Experiment 2, we used an acceptability judgment task and a word-picture verification task to compare the perceptual information that is activated by the comprehension of sentences describing an action using face-related objects near the face (near-sentence) or far from the face (far-sentence). Results showed that participants took a longer time to judge the acceptability of the far-sentence than the near-sentence. Verification times were significantly faster when the actions in the pictures matched the action described in the sentences than when they were mismatched. These findings suggest that action semantic knowledge influences sentence processing, and that perceptual information corresponding to the content of the sentence is activated regardless of the action semantic knowledge at the end of the sentence processing.
Jiang, Guoqian; Wang, Chen; Zhu, Qian; Chute, Christopher G
2013-01-01
Knowledge-driven text mining is becoming an important research area for identifying pharmacogenomics target genes. However, few of such studies have been focused on the pharmacogenomics targets of adverse drug events (ADEs). The objective of the present study is to build a framework of knowledge integration and discovery that aims to support pharmacogenomics target predication of ADEs. We integrate a semantically annotated literature corpus Semantic MEDLINE with a semantically coded ADE knowledgebase known as ADEpedia using a semantic web based framework. We developed a knowledge discovery approach combining a network analysis of a protein-protein interaction (PPI) network and a gene functional classification approach. We performed a case study of drug-induced long QT syndrome for demonstrating the usefulness of the framework in predicting potential pharmacogenomics targets of ADEs.
Type-specific proactive interference in patients with semantic and phonological STM deficits.
Harris, Lara; Olson, Andrew; Humphreys, Glyn
2014-01-01
Prior neuropsychological evidence suggests that semantic and phonological components of short-term memory (STM) are functionally and neurologically distinct. The current paper examines proactive interference (PI) from semantic and phonological information in two STM-impaired patients, DS (semantic STM deficit) and AK (phonological STM deficit). In Experiment 1 probe recognition tasks with open and closed sets of stimuli were used. Phonological PI was assessed using nonword items, and semantic and phonological PI was assessed using words. In Experiment 2 phonological and semantic PI was elicited by an item recognition probe test with stimuli that bore phonological and semantic relations to the probes. The data suggested heightened phonological PI for the semantic STM patient, and exaggerated effects of semantic PI in the phonological STM case. The findings are consistent with an account of extremely rapid decay of activated type-specific representations in cases of severely impaired phonological and semantic STM.
Thompson, Hannah E; Almaghyuli, Azizah; Noonan, Krist A; Barak, Ohr; Lambon Ralph, Matthew A; Jefferies, Elizabeth
2018-01-03
Semantic cognition, as described by the controlled semantic cognition (CSC) framework (Rogers et al., , Neuropsychologia, 76, 220), involves two key components: activation of coherent, generalizable concepts within a heteromodal 'hub' in combination with modality-specific features (spokes), and a constraining mechanism that manipulates and gates this knowledge to generate time- and task-appropriate behaviour. Executive-semantic goal representations, largely supported by executive regions such as frontal and parietal cortex, are thought to allow the generation of non-dominant aspects of knowledge when these are appropriate for the task or context. Semantic aphasia (SA) patients have executive-semantic deficits, and these are correlated with general executive impairment. If the CSC proposal is correct, patients with executive impairment should not only exhibit impaired semantic cognition, but should also show characteristics that align with those observed in SA. This possibility remains largely untested, as patients selected on the basis that they show executive impairment (i.e., with 'dysexecutive syndrome') have not been extensively tested on tasks tapping semantic control and have not been previously compared with SA cases. We explored conceptual processing in 12 patients showing symptoms consistent with dysexecutive syndrome (DYS) and 24 SA patients, using a range of multimodal semantic assessments which manipulated control demands. Patients with executive impairments, despite not being selected to show semantic impairments, nevertheless showed parallel patterns to SA cases. They showed strong effects of distractor strength, cues and miscues, and probe-target distance, plus minimal effects of word frequency on comprehension (unlike semantic dementia patients with degradation of conceptual knowledge). This supports a component process account of semantic cognition in which retrieval is shaped by control processes, and confirms that deficits in SA patients reflect difficulty controlling semantic retrieval. © 2018 The Authors. Journal of Neuropsychology published by John Wiley & Sons Ltd on behalf of British Psychological Society.
Palmiero, Massimiliano; Di Matteo, Rosalia; Belardinelli, Marta Olivetti
2014-05-01
Two experiments comparing imaginative processing in different modalities and semantic processing were carried out to investigate the issue of whether conceptual knowledge can be represented in different format. Participants were asked to judge the similarity between visual images, auditory images, and olfactory images in the imaginative block, if two items belonged to the same category in the semantic block. Items were verbally cued in both experiments. The degree of similarity between the imaginative and semantic items was changed across experiments. Experiment 1 showed that the semantic processing was faster than the visual and the auditory imaginative processing, whereas no differentiation was possible between the semantic processing and the olfactory imaginative processing. Experiment 2 revealed that only the visual imaginative processing could be differentiated from the semantic processing in terms of accuracy. These results showed that the visual and auditory imaginative processing can be differentiated from the semantic processing, although both visual and auditory images strongly rely on semantic representations. On the contrary, no differentiation is possible within the olfactory domain. Results are discussed in the frame of the imagery debate.
Bauer, Patricia J; Blue, Shala N; Xu, Aoxiang; Esposito, Alena G
2016-07-01
We investigated 7- to 10-year-old children's productive extension of semantic memory through self-generation of new factual knowledge derived through integration of separate yet related facts learned through instruction or through reading. In Experiment 1, an experimenter read the to-be-integrated facts. Children successfully learned and integrated the information and used it to further extend their semantic knowledge, as evidenced by high levels of correct responses in open-ended and forced-choice testing. In Experiment 2, on half of the trials, the to-be-integrated facts were read by an experimenter (as in Experiment 1) and on half of the trials, children read the facts themselves. Self-generation performance was high in both conditions (experimenter- and self-read); in both conditions, self-generation of new semantic knowledge was related to an independent measure of children's reading comprehension. In Experiment 3, the way children deployed cognitive resources during reading was predictive of their subsequent recall of newly learned information derived through integration. These findings indicate self-generation of new semantic knowledge through integration in school-age children as well as relations between this productive means of extension of semantic memory and cognitive processes engaged during reading. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Bauer, Patricia J.; Blue, Shala N.; Xu, Aoxiang; Esposito, Alena G.
2016-01-01
We investigated 7- to 10-year-old children’s productive extension of semantic memory through self-generation of new factual knowledge derived through integration of separate yet related facts learned through instruction or through reading. In Experiment 1, an experimenter read the to-be-integrated facts. Children successfully learned and integrated the information and used it to further extend their semantic knowledge, as evidenced by high levels of correct responses in open-ended and forced-choice testing. In Experiment 2, on half of the trials, the to-be-integrated facts were read by an experimenter (as in Experiment 1) and on half of the trials, children read the facts themselves. Self-generation performance was high in both conditions (experimenter- and self-read); in both conditions, self-generation of new semantic knowledge was related to an independent measure of children’s reading comprehension. In Experiment 3, the way children deployed cognitive resources during reading was predictive of their subsequent recall of newly learned information derived through integration. These findings indicate self-generation of new semantic knowledge through integration in school-age children as well as relations between this productive means of extension of semantic memory and cognitive processes engaged during reading. PMID:27253263
Woltz, Dan J; Gardner, Michael K
2015-09-01
Previous research has demonstrated a systematic, nonlinear relationship between word frequency judgments and values from word frequency norms. This relationship could reflect a perceptual process similar to that found in the psychophysics literature for a variety of sensory phenomena. Alternatively, it could reflect memory strength differences that are expected for words of varying levels of prior exposure. Two experiments tested the memory strength explanation by semantically priming words prior to frequency judgments. Exposure to related word meanings produced a small but measurable increase in target word frequency ratings. Repetition but not semantic priming had a greater impact on low compared to high frequency words. These findings are consistent with a memory strength view of frequency judgments that assumes a distributed network with lexical and semantic levels of representation. Copyright © 2015 Elsevier B.V. All rights reserved.
Campanella, Fabio; Fabbro, Franco; Urgesi, Cosimo
2013-01-01
Several studies have addressed the issue of how knowledge of common objects is organized in the brain, whereas the cognitive and anatomical underpinnings of familiar people knowledge have been less explored. Here we applied repetitive transcranial magnetic stimulation (rTMS) over the left and right temporal poles before asking healthy individuals to perform a speeded word-to-picture matching task using familiar people and common objects as stimuli. We manipulated two widely used semantic variables, namely the semantic distance and the familiarity of stimuli, to assess whether the semantic organization of familiar people knowledge is similar to that of common objects. For both objects and faces we reliably found semantic distance and familiarity effects, with less accurate and slower responses for stimulus pairs that were more closely related and less familiar. However, the effects of semantic variables differed across categories, with semantic distance effects larger for objects and familiarity effects larger for faces, suggesting that objects and faces might share a partially comparable organization of their semantic representations. The application of rTMS to the left temporal pole modulated, for both categories, semantic distance, but not familiarity effects, revealing that accessing object and face concepts might rely on overlapping processes within left anterior temporal regions. Crucially, rTMS of the left temporal pole affected only the recognition of pairs of stimuli that could be discriminated at specific levels of categorization (e.g., two kitchen tools or two famous persons), with no effect for discriminations at either superordinate or individual levels. Conversely, rTMS of the right temporal pole induced an overall slowing of reaction times that positively correlated with the visual similarity of the stimuli, suggesting a more perceptual rather than semantic role of the right anterior temporal regions. Results are discussed in the light of current models of face and object semantic representations in the brain. PMID:23704999
A Complex Network Approach to Distributional Semantic Models
Utsumi, Akira
2015-01-01
A number of studies on network analysis have focused on language networks based on free word association, which reflects human lexical knowledge, and have demonstrated the small-world and scale-free properties in the word association network. Nevertheless, there have been very few attempts at applying network analysis to distributional semantic models, despite the fact that these models have been studied extensively as computational or cognitive models of human lexical knowledge. In this paper, we analyze three network properties, namely, small-world, scale-free, and hierarchical properties, of semantic networks created by distributional semantic models. We demonstrate that the created networks generally exhibit the same properties as word association networks. In particular, we show that the distribution of the number of connections in these networks follows the truncated power law, which is also observed in an association network. This indicates that distributional semantic models can provide a plausible model of lexical knowledge. Additionally, the observed differences in the network properties of various implementations of distributional semantic models are consistently explained or predicted by considering the intrinsic semantic features of a word-context matrix and the functions of matrix weighting and smoothing. Furthermore, to simulate a semantic network with the observed network properties, we propose a new growing network model based on the model of Steyvers and Tenenbaum. The idea underlying the proposed model is that both preferential and random attachments are required to reflect different types of semantic relations in network growth process. We demonstrate that this model provides a better explanation of network behaviors generated by distributional semantic models. PMID:26295940
A semantic web framework to integrate cancer omics data with biological knowledge
2012-01-01
Background The RDF triple provides a simple linguistic means of describing limitless types of information. Triples can be flexibly combined into a unified data source we call a semantic model. Semantic models open new possibilities for the integration of variegated biological data. We use Semantic Web technology to explicate high throughput clinical data in the context of fundamental biological knowledge. We have extended Corvus, a data warehouse which provides a uniform interface to various forms of Omics data, by providing a SPARQL endpoint. With the querying and reasoning tools made possible by the Semantic Web, we were able to explore quantitative semantic models retrieved from Corvus in the light of systematic biological knowledge. Results For this paper, we merged semantic models containing genomic, transcriptomic and epigenomic data from melanoma samples with two semantic models of functional data - one containing Gene Ontology (GO) data, the other, regulatory networks constructed from transcription factor binding information. These two semantic models were created in an ad hoc manner but support a common interface for integration with the quantitative semantic models. Such combined semantic models allow us to pose significant translational medicine questions. Here, we study the interplay between a cell's molecular state and its response to anti-cancer therapy by exploring the resistance of cancer cells to Decitabine, a demethylating agent. Conclusions We were able to generate a testable hypothesis to explain how Decitabine fights cancer - namely, that it targets apoptosis-related gene promoters predominantly in Decitabine-sensitive cell lines, thus conveying its cytotoxic effect by activating the apoptosis pathway. Our research provides a framework whereby similar hypotheses can be developed easily. PMID:22373303
Semantic relatedness for evaluation of course equivalencies
NASA Astrophysics Data System (ADS)
Yang, Beibei
Semantic relatedness, or its inverse, semantic distance, measures the degree of closeness between two pieces of text determined by their meaning. Related work typically measures semantics based on a sparse knowledge base such as WordNet or Cyc that requires intensive manual efforts to build and maintain. Other work is based on a corpus such as the Brown corpus, or more recently, Wikipedia. This dissertation proposes two approaches to applying semantic relatedness to the problem of suggesting transfer course equivalencies. Two course descriptions are given as input to feed the proposed algorithms, which output a value that can be used to help determine if the courses are equivalent. The first proposed approach uses traditional knowledge sources such as WordNet and corpora for courses from multiple fields of study. The second approach uses Wikipedia, the openly-editable encyclopedia, and it focuses on courses from a technical field such as Computer Science. This work shows that it is promising to adapt semantic relatedness to the education field for matching equivalencies between transfer courses. A semantic relatedness measure using traditional knowledge sources such as WordNet performs relatively well on non-technical courses. However, due to the "knowledge acquisition bottleneck," such a resource is not ideal for technical courses, which use an extensive and growing set of technical terms. To address the problem, this work proposes a Wikipedia-based approach which is later shown to be more correlated to human judgment compared to previous work.
Adlof, Suzanne M; Patten, Hannah
2017-03-01
This study examined the unique and shared variance that nonword repetition and vocabulary knowledge contribute to children's ability to learn new words. Multiple measures of word learning were used to assess recall and recognition of phonological and semantic information. Fifty children, with a mean age of 8 years (range 5-12 years), completed experimental assessments of word learning and norm-referenced assessments of receptive and expressive vocabulary knowledge and nonword repetition skills. Hierarchical multiple regression analyses examined the variance in word learning that was explained by vocabulary knowledge and nonword repetition after controlling for chronological age. Together with chronological age, nonword repetition and vocabulary knowledge explained up to 44% of the variance in children's word learning. Nonword repetition was the stronger predictor of phonological recall, phonological recognition, and semantic recognition, whereas vocabulary knowledge was the stronger predictor of verbal semantic recall. These findings extend the results of past studies indicating that both nonword repetition skill and existing vocabulary knowledge are important for new word learning, but the relative influence of each predictor depends on the way word learning is measured. Suggestions for further research involving typically developing children and children with language or reading impairments are discussed.
Text-Content-Analysis based on the Syntactic Correlations between Ontologies
NASA Astrophysics Data System (ADS)
Tenschert, Axel; Kotsiopoulos, Ioannis; Koller, Bastian
The work presented in this chapter is concerned with the analysis of semantic knowledge structures, represented in the form of Ontologies, through which Service Level Agreements (SLAs) are enriched with new semantic data. The objective of the enrichment process is to enable SLA negotiation in a way that is much more convenient for a Service Users. For this purpose the deployment of an SLA-Management-System as well as the development of an analyzing procedure for Ontologies is required. This chapter will refer to the BREIN, the FinGrid and the LarKC projects. The analyzing procedure examines the syntactic correlations of several Ontologies whose focus lies in the field of mechanical engineering. A method of analyzing text and content is developed as part of this procedure. In order to so, we introduce a formalism as well as a method for understanding content. The analysis and methods are integrated to an SLA Management System which enables a Service User to interact with the system as a service by negotiating the user requests and including the semantic knowledge. Through negotiation between Service User and Service Provider the analysis procedure considers the user requests by extending the SLAs with semantic knowledge. Through this the economic use of an SLA-Management-System is increased by the enhancement of SLAs with semantic knowledge structures. The main focus of this chapter is the analyzing procedure, respectively the Text-Content-Analysis, which provides the mentioned semantic knowledge structures.
The influence of speech rate and accent on access and use of semantic information.
Sajin, Stanislav M; Connine, Cynthia M
2017-04-01
Circumstances in which the speech input is presented in sub-optimal conditions generally lead to processing costs affecting spoken word recognition. The current study indicates that some processing demands imposed by listening to difficult speech can be mitigated by feedback from semantic knowledge. A set of lexical decision experiments examined how foreign accented speech and word duration impact access to semantic knowledge in spoken word recognition. Results indicate that when listeners process accented speech, the reliance on semantic information increases. Speech rate was not observed to influence semantic access, except in the setting in which unusually slow accented speech was presented. These findings support interactive activation models of spoken word recognition in which attention is modulated based on speech demands.
Grilli, Matthew D
2017-11-01
Identity representations are higher-order knowledge structures that organise autobiographical memories on the basis of personality and role-based themes of one's self-concept. In two experiments, the extent to which different types of personal semantic content are reflected in these higher-order networks of memories was investigated. Healthy, young adult participants generated identity representations that varied in remoteness of formation and verbally reflected on these themes in an open-ended narrative task. The narrative responses were scored for retrieval of episodic, experience-near personal semantic and experience-far (i.e., abstract) personal semantic contents. Results revealed that to reflect on remotely formed identity representations, experience-far personal semantic contents were retrieved more than experience-near personal semantic contents. In contrast, to reflect on recently formed identity representations, experience-near personal semantic contents were retrieved more than experience-far personal semantic contents. Although episodic memory contents were retrieved less than both personal semantic content types to reflect on remotely formed identity representations, this content type was retrieved at a similar frequency as experience-far personal semantic content to reflect on recently formed identity representations. These findings indicate that the association of personal semantic content to identity representations is robust and related to time since acquisition of these knowledge structures.
Neural correlates of remembering/knowing famous people: an event-related fMRI study.
Denkova, Ekaterina; Botzung, Anne; Manning, Lilianne
2006-01-01
It has been suggested that knowledge about some famous people depends on both a generic semantic component and an autobiographical component [Westmacott, R., & Moscovitch, M. (2003). The contribution of autobiographical significance to semantic memory. Memory and Cognition, 31, 761-774]. The neuropsychological studies of semantic dementia (SD) and Alzheimer disease (AD) demonstrated that the two aspects are very likely to be mediated by different brain structures, with the episodic component being highly dependent upon the integrity of the medial temporal lobe (MTL) [Westmacott, R., Black, S. E., Freedman, M., & Moscovitch, M. (2004). The contribution of autobiographical significance to semantic memory: Evidence from Alzheimer's disease, semantic dementia, and amnesia. Neuropsychologia, 42, 25-48]. Using an fMRI design in healthy participants, we aimed: (i) to investigate the pattern of brain activations sustaining the autobiographical and the semantic aspects of knowledge about famous persons. Moreover, (ii) we examined if the stimulus material (face/name) influences the lateralisation of the cerebral networks. Our findings suggested that different patterns of activation corresponded to the presence or absence of personal significance linked to semantic knowledge; MTL was engaged only in the former case. Although choice of stimulus material did not influence the hemispheric lateralisation in "classical" terms, it did play a role in engaging different cerebral regions.
Relative category-specific preservation in semantic dementia? Evidence from 35 cases.
Merck, Catherine; Jonin, Pierre-Yves; Vichard, Hélène; Boursiquot, Sandrine Le Moal; Leblay, Virginie; Belliard, Serge
2013-03-01
Category-specific deficits have rarely been reported in semantic dementia (SD). To our knowledge, only four previous studies have documented category-specific deficits, and these have focused on the living versus non-living things contrast rather than on more fine-grained semantic categories. This study aimed to determine whether a category-specific effect could be highlighted by a semantic sorting task administered to 35 SD patients once at baseline and again after 2 years and to 10 Alzheimer's disease patients (AD). We found a relative preservation of fruit and vegetables only in SD. This relative preservation of fruit and vegetables could be considered with regard to the importance of color knowledge in their discrimination. Indeed, color knowledge retrieval is known to depend on the left posterior fusiform gyrus which is relatively spared in SD. Finally, according to predictions of semantic memory models, our findings best fitted the Devlin and Gonnerman's computational account. Copyright © 2013 Elsevier Inc. All rights reserved.
To ontologise or not to ontologise: An information model for a geospatial knowledge infrastructure
NASA Astrophysics Data System (ADS)
Stock, Kristin; Stojanovic, Tim; Reitsma, Femke; Ou, Yang; Bishr, Mohamed; Ortmann, Jens; Robertson, Anne
2012-08-01
A geospatial knowledge infrastructure consists of a set of interoperable components, including software, information, hardware, procedures and standards, that work together to support advanced discovery and creation of geoscientific resources, including publications, data sets and web services. The focus of the work presented is the development of such an infrastructure for resource discovery. Advanced resource discovery is intended to support scientists in finding resources that meet their needs, and focuses on representing the semantic details of the scientific resources, including the detailed aspects of the science that led to the resource being created. This paper describes an information model for a geospatial knowledge infrastructure that uses ontologies to represent these semantic details, including knowledge about domain concepts, the scientific elements of the resource (analysis methods, theories and scientific processes) and web services. This semantic information can be used to enable more intelligent search over scientific resources, and to support new ways to infer and visualise scientific knowledge. The work describes the requirements for semantic support of a knowledge infrastructure, and analyses the different options for information storage based on the twin goals of semantic richness and syntactic interoperability to allow communication between different infrastructures. Such interoperability is achieved by the use of open standards, and the architecture of the knowledge infrastructure adopts such standards, particularly from the geospatial community. The paper then describes an information model that uses a range of different types of ontologies, explaining those ontologies and their content. The information model was successfully implemented in a working geospatial knowledge infrastructure, but the evaluation identified some issues in creating the ontologies.
Explaining semantic short-term memory deficits: Evidence for the critical role of semantic control
Hoffman, Paul; Jefferies, Elizabeth; Lambon Ralph, Matthew A.
2011-01-01
Patients with apparently selective short-term memory (STM) deficits for semantic information have played an important role in developing multi-store theories of STM and challenge the idea that verbal STM is supported by maintaining activation in the language system. We propose that semantic STM deficits are not as selective as previously thought and can occur as a result of mild disruption to semantic control processes, i.e., mechanisms that bias semantic processing towards task-relevant aspects of knowledge and away from irrelevant information. We tested three semantic STM patients with tasks that tapped four aspects of semantic control: (i) resolving ambiguity between word meanings, (ii) sensitivity to cues, (iii) ignoring irrelevant information and (iv) detecting weak semantic associations. All were impaired in conditions requiring more semantic control, irrespective of the STM demands of the task, suggesting a mild, but task-general, deficit in regulating semantic knowledge. This mild deficit has a disproportionate effect on STM tasks because they have high intrinsic control demands: in STM tasks, control is required to keep information active when it is no longer available in the environment and to manage competition between items held in memory simultaneously. By re-interpreting the core deficit in semantic STM patients in this way, we are able to explain their apparently selective impairment without the need for a specialised STM store. Instead, we argue that semantic STM patients occupy the mildest end of spectrum of semantic control disorders. PMID:21195105
Premorbid expertise produces category-specific impairment in a domain-general semantic disorder.
Jefferies, Elizabeth; Rogers, Timothy T; Ralph, Matthew A Lambon
2011-10-01
For decades, category-specific semantic impairment - i.e., better comprehension of items from one semantic category than another - has been the driving force behind many claims about the organisation of conceptual knowledge in the brain. Double dissociations between patients with category-specific disorders are widely interpreted as showing that different conceptual domains are necessarily supported by functionally independent systems. We show that, to the contrary, even strong or classical dissociations can also arise from individual differences in premorbid expertise. We examined two patients with global and progressive semantic degradation who, unusually, had known areas of premorbid expertise. Patient 1, a former automotive worker, showed selective preservation of car knowledge, whereas Patient 2, a former botanist, showed selective preservation of information about plants. In non-expert domains, these patients showed the typical pattern: i.e., an inability to differentiate between highly similar concepts (e.g., rose and daisy), but retention of broader distinctions (e.g., between rose and cat). Parallel distributed processing (PDP) models of semantic cognition show that expertise in a particular domain increases the differentiation of specific-level concepts, such that the semantic distance between these items resembles non-expert basic-level distinctions. We propose that these structural changes interact with global semantic degradation, particularly when expert knowledge is acquired early and when exposure to expert concepts continues during disease progression. Therefore, category-specific semantic impairment can arise from at least two distinct mechanisms: damage to representations that are critical for a particular category (e.g., knowledge of hand shape and action for the category 'tools') and differences in premorbid experience. Copyright © 2011 Elsevier Ltd. All rights reserved.
Object knowledge changes visual appearance: semantic effects on color afterimages.
Lupyan, Gary
2015-10-01
According to predictive coding models of perception, what we see is determined jointly by the current input and the priors established by previous experience, expectations, and other contextual factors. The same input can thus be perceived differently depending on the priors that are brought to bear during viewing. Here, I show that expected (diagnostic) colors are perceived more vividly than arbitrary or unexpected colors, particularly when color input is unreliable. Participants were tested on a version of the 'Spanish Castle Illusion' in which viewing a hue-inverted image renders a subsequently shown achromatic version of the image in vivid color. Adapting to objects with intrinsic colors (e.g., a pumpkin) led to stronger afterimages than adapting to arbitrarily colored objects (e.g., a pumpkin-colored car). Considerably stronger afterimages were also produced by scenes containing intrinsically colored elements (grass, sky) compared to scenes with arbitrarily colored objects (books). The differences between images with diagnostic and arbitrary colors disappeared when the association between the image and color priors was weakened by, e.g., presenting the image upside-down, consistent with the prediction that color appearance is being modulated by color knowledge. Visual inputs that conflict with prior knowledge appear to be phenomenologically discounted, but this discounting is moderated by input certainty, as shown by the final study which uses conventional images rather than afterimages. As input certainty is increased, unexpected colors can become easier to detect than expected ones, a result consistent with predictive-coding models. Copyright © 2015 Elsevier B.V. All rights reserved.
COTARD SYNDROME IN SEMANTIC DEMENTIA
Mendez, Mario F.; Ramírez-Bermúdez, Jesús
2011-01-01
Background Semantic dementia is a neurodegenerative disorder characterized by the loss of meaning of words or concepts. semantic dementia can offer potential insights into the mechanisms of content-specific delusions. Objective The authors present a rare case of semantic dementia with Cotard syndrome, a delusion characterized by nihilism or self-negation. Method The semantic deficits and other features of semantic dementia were evaluated in relation to the patient's Cotard syndrome. Results Mrs. A developed the delusional belief that she was wasting and dying. This occurred after she lost knowledge for her somatic discomforts and sensations and for the organs that were the source of these sensations. Her nihilistic beliefs appeared to emerge from her misunderstanding of her somatic sensations. Conclusion This unique patient suggests that a mechanism for Cotard syndrome is difficulty interpreting the nature and source of internal pains and sensations. We propose that loss of semantic knowledge about one's own body may lead to the delusion of nihilism or death. PMID:22054629
ERIC Educational Resources Information Center
Marczinski, Cecile A.; Kertesz, Andrew
2006-01-01
This study examined the impact of various degenerative dementias on access to semantic knowledge and the status of semantic representations. Patients with semantic dementia, primary progressive aphasia, and Alzheimer's disease were compared with elderly controls on tasks of category and letter fluency, with number of words generated, mean lexical…
Semantic categorization: a comparison between deaf and hearing children.
Ormel, Ellen A; Gijsel, Martine A R; Hermans, Daan; Bosman, Anna M T; Knoors, Harry; Verhoeven, Ludo
2010-01-01
Learning to read is a major obstacle for children who are deaf. The otherwise significant role of phonology is often limited as a result of hearing loss. However, semantic knowledge may facilitate reading comprehension. One important aspect of semantic knowledge concerns semantic categorization. In the present study, the quality of the semantic categorization of both deaf and hearing children was examined for written words and pictures at two categorization levels. The deaf children performed better at the picture condition compared to the written word condition, while the hearing children performed similarly at pictures and written words. The hearing children outperformed the deaf children, in particular for written words. In addition, the results of the deaf children for the written words correlated to their sign vocabulary and sign language comprehension. The increase in semantic categorization was limited across elementary school grade levels. Readers will be able to: (1) understand several semantic categorization differences between groups of deaf and hearing children; (2) describe factors that may affect the development of semantic categorization, in particular the relationship between sign language skills and semantic categorization for deaf children. Copyright 2010 Elsevier Inc. All rights reserved.
Monnier, Catherine; Bonthoux, Françoise
2011-11-01
The present research was designed to highlight the relation between children's categorical knowledge and their verbal short-term memory (STM) performance. To do this, we manipulated the categorical organization of the words composing lists to be memorized by 5- and 9-year-old children. Three types of word list were drawn up: semantically similar context-dependent (CD) lists, semantically similar context-independent (CI) lists, and semantically dissimilar lists. In line with the procedure used by Poirier and Saint-Aubin (1995), the dissimilar lists were produced using words from the semantically similar lists. Both 5- and 9-year-old children showed better recall for the semantically similar CD lists than they did for the unrelated lists. In the semantic similar CI condition, semantic similarity enhanced immediate serial recall only at age 9 but contributed to item information memory both at ages 5 and 9. These results, which indicate a semantic influence of long-term memory (LTM) on serial recall from age 5, are discussed in the light of current models of STM. Moreover, we suggest that differences between results at 5 and 9 years are compatible with pluralist models of development. ©2011 The British Psychological Society.
Piolino, Pascale; Lamidey, Virginie; Desgranges, Béatrice; Eustache, Francis
2007-01-01
Fifty-two subjects between ages 40 and 79 years were administered a questionnaire assessing their ability to recall semantic information about famous people from 4 different decades and to recollect its episodic source of acquisition together with autonoetic consciousness via the remember-know paradigm. In addition, they underwent a battery of standardized neuropsychological tests to assess episodic and semantic memory and executive functions. The analyses of age reveal differences for the episodic source score but no differences between age groups for the semantic scores within each decade. Regardless of the age of people, the analyses also show that semantic memory subcomponents of the famous person test are highly associated with each other as well as with the source component. The recall of semantic information on the famous person test relies on participants' semantic abilities, whereas the recall of its episodic source depends on their executive functions. The present findings confirm the existence of an episodic-semantic distinction in knowledge about famous people. They provide further evidence that personal source and semantic information are at once distinct and highly interactive within the framework of remote memory. (c) 2007 APA, all rights reserved.
Exploiting Recurring Structure in a Semantic Network
NASA Technical Reports Server (NTRS)
Wolfe, Shawn R.; Keller, Richard M.
2004-01-01
With the growing popularity of the Semantic Web, an increasing amount of information is becoming available in machine interpretable, semantically structured networks. Within these semantic networks are recurring structures that could be mined by existing or novel knowledge discovery methods. The mining of these semantic structures represents an interesting area that focuses on mining both for and from the Semantic Web, with surprising applicability to problems confronting the developers of Semantic Web applications. In this paper, we present representative examples of recurring structures and show how these structures could be used to increase the utility of a semantic repository deployed at NASA.
Semantic memory in developmental amnesia.
Elward, Rachael L; Vargha-Khadem, Faraneh
2018-04-30
Patients with developmental amnesia resulting from bilateral hippocampal atrophy associated with neonatal hypoxia-ischaemia typically show relatively preserved semantic memory and factual knowledge about the natural world despite severe impairments in episodic memory. Understanding the neural and mnemonic processes that enable this context-free semantic knowledge to be acquired throughout development without the support of the contextualised episodic memory system is a serious challenge. This review describes the clinical presentation of patients with developmental amnesia, contrasts its features with those reported for adult-onset hippocampal amnesia, and analyses the effects of variables that influence the learning of new semantic information. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.
ERIC Educational Resources Information Center
Pirnay-Dummer, Pablo
2015-01-01
A local semantic trace is a certain quasi-propositional structure that can still be reconstructed from written content that is incomplete or does not follow a proper grammar. It can also retrace bits of knowledge from text containing only very few words, making the microstructure of these artifacts of knowledge externalization available for…
Linked Registries: Connecting Rare Diseases Patient Registries through a Semantic Web Layer
González-Castro, Lorena; Carta, Claudio; van der Horst, Eelke; Lopes, Pedro; Kaliyaperumal, Rajaram; Thompson, Mark; Thompson, Rachel; Queralt-Rosinach, Núria; Lopez, Estrella; Wood, Libby; Robertson, Agata; Lamanna, Claudia; Gilling, Mette; Orth, Michael; Merino-Martinez, Roxana; Taruscio, Domenica; Lochmüller, Hanns
2017-01-01
Patient registries are an essential tool to increase current knowledge regarding rare diseases. Understanding these data is a vital step to improve patient treatments and to create the most adequate tools for personalized medicine. However, the growing number of disease-specific patient registries brings also new technical challenges. Usually, these systems are developed as closed data silos, with independent formats and models, lacking comprehensive mechanisms to enable data sharing. To tackle these challenges, we developed a Semantic Web based solution that allows connecting distributed and heterogeneous registries, enabling the federation of knowledge between multiple independent environments. This semantic layer creates a holistic view over a set of anonymised registries, supporting semantic data representation, integrated access, and querying. The implemented system gave us the opportunity to answer challenging questions across disperse rare disease patient registries. The interconnection between those registries using Semantic Web technologies benefits our final solution in a way that we can query single or multiple instances according to our needs. The outcome is a unique semantic layer, connecting miscellaneous registries and delivering a lightweight holistic perspective over the wealth of knowledge stemming from linked rare disease patient registries. PMID:29214177
Linked Registries: Connecting Rare Diseases Patient Registries through a Semantic Web Layer.
Sernadela, Pedro; González-Castro, Lorena; Carta, Claudio; van der Horst, Eelke; Lopes, Pedro; Kaliyaperumal, Rajaram; Thompson, Mark; Thompson, Rachel; Queralt-Rosinach, Núria; Lopez, Estrella; Wood, Libby; Robertson, Agata; Lamanna, Claudia; Gilling, Mette; Orth, Michael; Merino-Martinez, Roxana; Posada, Manuel; Taruscio, Domenica; Lochmüller, Hanns; Robinson, Peter; Roos, Marco; Oliveira, José Luís
2017-01-01
Patient registries are an essential tool to increase current knowledge regarding rare diseases. Understanding these data is a vital step to improve patient treatments and to create the most adequate tools for personalized medicine. However, the growing number of disease-specific patient registries brings also new technical challenges. Usually, these systems are developed as closed data silos, with independent formats and models, lacking comprehensive mechanisms to enable data sharing. To tackle these challenges, we developed a Semantic Web based solution that allows connecting distributed and heterogeneous registries, enabling the federation of knowledge between multiple independent environments. This semantic layer creates a holistic view over a set of anonymised registries, supporting semantic data representation, integrated access, and querying. The implemented system gave us the opportunity to answer challenging questions across disperse rare disease patient registries. The interconnection between those registries using Semantic Web technologies benefits our final solution in a way that we can query single or multiple instances according to our needs. The outcome is a unique semantic layer, connecting miscellaneous registries and delivering a lightweight holistic perspective over the wealth of knowledge stemming from linked rare disease patient registries.
Amalric, Marie; Dehaene, Stanislas
2017-02-19
Is mathematical language similar to natural language? Are language areas used by mathematicians when they do mathematics? And does the brain comprise a generic semantic system that stores mathematical knowledge alongside knowledge of history, geography or famous people? Here, we refute those views by reviewing three functional MRI studies of the representation and manipulation of high-level mathematical knowledge in professional mathematicians. The results reveal that brain activity during professional mathematical reflection spares perisylvian language-related brain regions as well as temporal lobe areas classically involved in general semantic knowledge. Instead, mathematical reflection recycles bilateral intraparietal and ventral temporal regions involved in elementary number sense. Even simple fact retrieval, such as remembering that 'the sine function is periodical' or that 'London buses are red', activates dissociated areas for math versus non-math knowledge. Together with other fMRI and recent intracranial studies, our results indicated a major separation between two brain networks for mathematical and non-mathematical semantics, which goes a long way to explain a variety of facts in neuroimaging, neuropsychology and developmental disorders.This article is part of a discussion meeting issue 'The origins of numerical abilities'. © 2017 The Author(s).
Frishkoff, Gwen A; Perfetti, Charles A; Westbury, Chris
2009-01-01
This study examines the sensitivity of early event-related potentials (ERPs) to degrees of word semantic knowledge. Participants with strong, average, or weak vocabulary skills made speeded lexical decisions to letter strings. To represent the full spectrum of word knowledge among adult native-English speakers, we used rare words that were orthographically matched with more familiar words and with pseudowords. Since the lexical decision could not reliably be made on the basis of word form, subjects were obliged to use semantic knowledge to perform the task. A d' analysis suggested that high-skilled subjects adopted a more conservative strategy in response to rare versus more familiar words. Moreover, the high-skilled participants showed a trend towards an enhanced "N2c" to rare words, and a similar posterior temporal effect reached significance approximately 650 ms. Generators for these effects were localized to left temporal cortex. We discuss implications of these results for word learning and for theories of lexical semantic access.
Auditing Associative Relations across Two Knowledge Sources
Vizenor, Lowell T.; Bodenreider, Olivier; McCray, Alexa T.
2009-01-01
Objectives This paper proposes a novel semantic method for auditing associative relations in biomedical terminologies. We tested our methodology on two Unified Medical Language System (UMLS) knowledge sources. Methods We use the UMLS semantic groups as high-level representations of the domain and range of relationships in the Metathesaurus and in the Semantic Network. A mapping created between Metathesaurus relationships and Semantic Network relationships forms the basis for comparing the signatures of a given Metathesaurus relationship to the signatures of the semantic relationship to which it is mapped. The consistency of Metathesaurus relations is studied for each relationship. Results Of the 177 associative relationships in the Metathesaurus, 84 (48%) exhibit a high degree of consistency with the corresponding Semantic Network relationships. Overall, 63% of the 1.8M associative relations in the Metathesaurus are consistent with relations in the Semantic Network. Conclusion The semantics of associative relationships in biomedical terminologies should be defined explicitly by their developers. The Semantic Network would benefit from being extended with new relationships and with new relations for some existing relationships. The UMLS editing environment could take advantage of the correspondence established between relationships in the Metathesaurus and the Semantic Network. Finally, the auditing method also yielded useful information for refining the mapping of associative relationships between the two sources. PMID:19475724
2003-03-01
information technologies that can: (a) represent knowledge and skills, (b) identify people with all or parts of the knowledge and task experience...needed but lacked, A might be at too advanced a level for the 8 individual to understand given his or her previous knowledge , B might overlap too...SEMANTIC ANALYSIS-BASED TECHNOLOGY Darrell Laham Knowledge Analysis Technologies 4940 Pearl East Circle #200 Boulder, CO 80301 Winston
Benchmark eye movement effects during natural reading in autism spectrum disorder.
Howard, Philippa L; Liversedge, Simon P; Benson, Valerie
2017-01-01
In 2 experiments, eye tracking methodology was used to assess on-line lexical, syntactic and semantic processing in autism spectrum disorder (ASD). In Experiment 1, lexical identification was examined by manipulating the frequency of target words. Both typically developed (TD) and ASD readers showed normal frequency effects, suggesting that the processes TD and ASD readers engage in to identify words are comparable. In Experiment 2, syntactic parsing and semantic interpretation requiring the on-line use of world knowledge were examined, by having participants read garden path sentences containing an ambiguous prepositional phrase. Both groups showed normal garden path effects when reading low-attached sentences and the time course of reading disruption was comparable between groups. This suggests that not only do ASD readers hold similar syntactic preferences to TD readers, but also that they use world knowledge on-line during reading. Together, these experiments demonstrate that the initial construction of sentence interpretation appears to be intact in ASD. However, the finding that ASD readers skip target words less often in Experiment 2, and take longer to read sentences during second pass for both experiments, suggests that they adopt a more cautious reading strategy and take longer to evaluate their sentence interpretation prior to making a manual response. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Knowledge Discovery from Biomedical Ontologies in Cross Domains.
Shen, Feichen; Lee, Yugyung
2016-01-01
In recent years, there is an increasing demand for sharing and integration of medical data in biomedical research. In order to improve a health care system, it is required to support the integration of data by facilitating semantic interoperability systems and practices. Semantic interoperability is difficult to achieve in these systems as the conceptual models underlying datasets are not fully exploited. In this paper, we propose a semantic framework, called Medical Knowledge Discovery and Data Mining (MedKDD), that aims to build a topic hierarchy and serve the semantic interoperability between different ontologies. For the purpose, we fully focus on the discovery of semantic patterns about the association of relations in the heterogeneous information network representing different types of objects and relationships in multiple biological ontologies and the creation of a topic hierarchy through the analysis of the discovered patterns. These patterns are used to cluster heterogeneous information networks into a set of smaller topic graphs in a hierarchical manner and then to conduct cross domain knowledge discovery from the multiple biological ontologies. Thus, patterns made a greater contribution in the knowledge discovery across multiple ontologies. We have demonstrated the cross domain knowledge discovery in the MedKDD framework using a case study with 9 primary biological ontologies from Bio2RDF and compared it with the cross domain query processing approach, namely SLAP. We have confirmed the effectiveness of the MedKDD framework in knowledge discovery from multiple medical ontologies.
Knowledge Discovery from Biomedical Ontologies in Cross Domains
Shen, Feichen; Lee, Yugyung
2016-01-01
In recent years, there is an increasing demand for sharing and integration of medical data in biomedical research. In order to improve a health care system, it is required to support the integration of data by facilitating semantic interoperability systems and practices. Semantic interoperability is difficult to achieve in these systems as the conceptual models underlying datasets are not fully exploited. In this paper, we propose a semantic framework, called Medical Knowledge Discovery and Data Mining (MedKDD), that aims to build a topic hierarchy and serve the semantic interoperability between different ontologies. For the purpose, we fully focus on the discovery of semantic patterns about the association of relations in the heterogeneous information network representing different types of objects and relationships in multiple biological ontologies and the creation of a topic hierarchy through the analysis of the discovered patterns. These patterns are used to cluster heterogeneous information networks into a set of smaller topic graphs in a hierarchical manner and then to conduct cross domain knowledge discovery from the multiple biological ontologies. Thus, patterns made a greater contribution in the knowledge discovery across multiple ontologies. We have demonstrated the cross domain knowledge discovery in the MedKDD framework using a case study with 9 primary biological ontologies from Bio2RDF and compared it with the cross domain query processing approach, namely SLAP. We have confirmed the effectiveness of the MedKDD framework in knowledge discovery from multiple medical ontologies. PMID:27548262
Metusalem, Ross; Kutas, Marta; Urbach, Thomas P.; Elman, Jeffrey L.
2016-01-01
During incremental language comprehension, the brain activates knowledge of described events, including knowledge elements that constitute semantic anomalies in their linguistic context. The present study investigates hemispheric asymmetries in this process, with the aim of advancing our understanding of the neural basis and functional properties of event knowledge activation during incremental comprehension. In a visual half-field event-related brain potential (ERP) experiment, participants read brief discourses in which the third sentence contained a word that was either highly expected, semantically anomalous but related to the described event, or semantically anomalous but unrelated to the described event. For both visual fields of target word presentation, semantically anomalous words elicited N400 ERP components of greater amplitude than did expected words. Crucially, event-related anomalous words elicited a reduced N400 relative to event-unrelated anomalous words only with left visual field/right hemisphere presentation. This result suggests that right hemisphere processes are critical to the activation of event knowledge elements that violate the linguistic context, and in doing so informs existing theories of hemispheric asymmetries in semantic processing during language comprehension. Additionally, this finding coincides with past research suggesting a crucial role for the right hemisphere in elaborative inference generation, raises interesting questions regarding hemispheric coordination in generating event-specific linguistic expectancies, and more generally highlights the possibility of functional dissociation between event knowledge activation for the generation of elaborative inferences and for linguistic expectancies. PMID:26878980
Metusalem, Ross; Kutas, Marta; Urbach, Thomas P; Elman, Jeffrey L
2016-04-01
During incremental language comprehension, the brain activates knowledge of described events, including knowledge elements that constitute semantic anomalies in their linguistic context. The present study investigates hemispheric asymmetries in this process, with the aim of advancing our understanding of the neural basis and functional properties of event knowledge activation during incremental comprehension. In a visual half-field event-related brain potential (ERP) experiment, participants read brief discourses in which the third sentence contained a word that was either highly expected, semantically anomalous but related to the described event (Event-Related), or semantically anomalous but unrelated to the described event (Event-Unrelated). For both visual fields of target word presentation, semantically anomalous words elicited N400 ERP components of greater amplitude than did expected words. Crucially, Event-Related anomalous words elicited a reduced N400 relative to Event-Unrelated anomalous words only with left visual field/right hemisphere presentation. This result suggests that right hemisphere processes are critical to the activation of event knowledge elements that violate the linguistic context, and in doing so informs existing theories of hemispheric asymmetries in semantic processing during language comprehension. Additionally, this finding coincides with past research suggesting a crucial role for the right hemisphere in elaborative inference generation, raises interesting questions regarding hemispheric coordination in generating event-specific linguistic expectancies, and more generally highlights the possibility of functional dissociation of event knowledge activation for the generation of elaborative inferences and for linguistic expectancies. Copyright © 2016 Elsevier Ltd. All rights reserved.
Patten, Hannah
2017-01-01
Purpose This study examined the unique and shared variance that nonword repetition and vocabulary knowledge contribute to children's ability to learn new words. Multiple measures of word learning were used to assess recall and recognition of phonological and semantic information. Method Fifty children, with a mean age of 8 years (range 5–12 years), completed experimental assessments of word learning and norm-referenced assessments of receptive and expressive vocabulary knowledge and nonword repetition skills. Hierarchical multiple regression analyses examined the variance in word learning that was explained by vocabulary knowledge and nonword repetition after controlling for chronological age. Results Together with chronological age, nonword repetition and vocabulary knowledge explained up to 44% of the variance in children's word learning. Nonword repetition was the stronger predictor of phonological recall, phonological recognition, and semantic recognition, whereas vocabulary knowledge was the stronger predictor of verbal semantic recall. Conclusions These findings extend the results of past studies indicating that both nonword repetition skill and existing vocabulary knowledge are important for new word learning, but the relative influence of each predictor depends on the way word learning is measured. Suggestions for further research involving typically developing children and children with language or reading impairments are discussed. PMID:28241284
Semantic Relatedness for Evaluation of Course Equivalencies
ERIC Educational Resources Information Center
Yang, Beibei
2012-01-01
Semantic relatedness, or its inverse, semantic distance, measures the degree of closeness between two pieces of text determined by their meaning. Related work typically measures semantics based on a sparse knowledge base such as WordNet or Cyc that requires intensive manual efforts to build and maintain. Other work is based on a corpus such as the…
Investigating implicit knowledge in ontologies with application to the anatomical domain.
Zhang, S; Bodenreider, O
2004-01-01
Knowledge in biomedical ontologies can be explicitly represented (often by means of semantic relations), but may also be implicit, i.e., embedded in the concept names and inferable from various combinations of semantic relations. This paper investigates implicit knowledge in two ontologies of anatomy: the Foundational Model of Anatomy and GALEN. The methods consist of extracting the knowledge explicitly represented, acquiring the implicit knowledge through augmentation and inference techniques, and identifying the origin of each semantic relation. The number of relations (12 million in FMA and 4.6 million in GALEN), broken down by source, is presented. Major findings include: each technique provides specific relations; and many relations can be generated by more than one technique. The application of these findings to ontology auditing, validation, and maintenance is discussed, as well as the application to ontology integration.
A neural basis for category and modality specificity of semantic knowledge.
Thompson-Schill, S L; Aguirre, G K; D'Esposito, M; Farah, M J
1999-06-01
Prevalent theories hold that semantic memory is organized by sensorimotor modality (e.g., visual knowledge, motor knowledge). While some neuroimaging studies support this idea, it cannot account for the category specific (e.g., living things) knowledge impairments seen in some brain damaged patients that cut across modalities. In this article we test an alternative model of how damage to interactive, modality-specific neural regions might give rise to these categorical impairments. Functional MRI was used to examine a cortical area with a known modality-specific function during the retrieval of visual and non-visual knowledge about living and non-living things. The specific predictions of our model regarding the signal observed in this area were confirmed, supporting the notion that semantic memory is functionally segregated into anatomically discrete, but highly interactive, modality-specific regions.
Jointly Constructing Semantic Waves: Implications for Teacher Training
ERIC Educational Resources Information Center
Macnaught, Lucy; Maton, Karl; Martin, J. R.; Matruglio, Erika
2013-01-01
This paper addresses how teachers can be trained to enable cumulative knowledge-building. It focuses on the final intervention stage of the "Disciplinarity, Knowledge and Schooling" ("DISKS") project at the University of Sydney. In this special issue, Maton identifies "semantic waves" as a crucial characteristic of…
Temporal Representation in Semantic Graphs
DOE Office of Scientific and Technical Information (OSTI.GOV)
Levandoski, J J; Abdulla, G M
2007-08-07
A wide range of knowledge discovery and analysis applications, ranging from business to biological, make use of semantic graphs when modeling relationships and concepts. Most of the semantic graphs used in these applications are assumed to be static pieces of information, meaning temporal evolution of concepts and relationships are not taken into account. Guided by the need for more advanced semantic graph queries involving temporal concepts, this paper surveys the existing work involving temporal representations in semantic graphs.
ERIC Educational Resources Information Center
Nilforoushan, Somayeh
2012-01-01
This study focused on the effect of teaching vocabulary through semantic mapping on the awareness of two affective dimensions, evaluation and potency dimensions of deep vocabulary knowledge as well as the general vocabulary knowledge of EFL students. Sixty intermediate EFL female adult learners participated in this study; they were chosen among 90…
A User-Centric Knowledge Creation Model in a Web of Object-Enabled Internet of Things Environment
Kibria, Muhammad Golam; Fattah, Sheik Mohammad Mostakim; Jeong, Kwanghyeon; Chong, Ilyoung; Jeong, Youn-Kwae
2015-01-01
User-centric service features in a Web of Object-enabled Internet of Things environment can be provided by using a semantic ontology that classifies and integrates objects on the World Wide Web as well as shares and merges context-aware information and accumulated knowledge. The semantic ontology is applied on a Web of Object platform to virtualize the real world physical devices and information to form virtual objects that represent the features and capabilities of devices in the virtual world. Detailed information and functionalities of multiple virtual objects are combined with service rules to form composite virtual objects that offer context-aware knowledge-based services, where context awareness plays an important role in enabling automatic modification of the system to reconfigure the services based on the context. Converting the raw data into meaningful information and connecting the information to form the knowledge and storing and reusing the objects in the knowledge base can both be expressed by semantic ontology. In this paper, a knowledge creation model that synchronizes a service logistic model and a virtual world knowledge model on a Web of Object platform has been proposed. To realize the context-aware knowledge-based service creation and execution, a conceptual semantic ontology model has been developed and a prototype has been implemented for a use case scenario of emergency service. PMID:26393609
A User-Centric Knowledge Creation Model in a Web of Object-Enabled Internet of Things Environment.
Kibria, Muhammad Golam; Fattah, Sheik Mohammad Mostakim; Jeong, Kwanghyeon; Chong, Ilyoung; Jeong, Youn-Kwae
2015-09-18
User-centric service features in a Web of Object-enabled Internet of Things environment can be provided by using a semantic ontology that classifies and integrates objects on the World Wide Web as well as shares and merges context-aware information and accumulated knowledge. The semantic ontology is applied on a Web of Object platform to virtualize the real world physical devices and information to form virtual objects that represent the features and capabilities of devices in the virtual world. Detailed information and functionalities of multiple virtual objects are combined with service rules to form composite virtual objects that offer context-aware knowledge-based services, where context awareness plays an important role in enabling automatic modification of the system to reconfigure the services based on the context. Converting the raw data into meaningful information and connecting the information to form the knowledge and storing and reusing the objects in the knowledge base can both be expressed by semantic ontology. In this paper, a knowledge creation model that synchronizes a service logistic model and a virtual world knowledge model on a Web of Object platform has been proposed. To realize the context-aware knowledge-based service creation and execution, a conceptual semantic ontology model has been developed and a prototype has been implemented for a use case scenario of emergency service.
Renoult, Louis; Tanguay, Annick; Beaudry, Myriam; Tavakoli, Paniz; Rabipour, Sheida; Campbell, Kenneth; Moscovitch, Morris; Levine, Brian; Davidson, Patrick S R
2016-03-01
Declarative memory is thought to consist of two independent systems: episodic and semantic. Episodic memory represents personal and contextually unique events, while semantic memory represents culturally-shared, acontextual factual knowledge. Personal semantics refers to aspects of declarative memory that appear to fall somewhere in between the extremes of episodic and semantic. Examples include autobiographical knowledge and memories of repeated personal events. These two aspects of personal semantics have been studied little and rarely compared to both semantic and episodic memory. We recorded the event-related potentials (ERPs) of 27 healthy participants while they verified the veracity of sentences probing four types of questions: general (i.e., semantic) facts, autobiographical facts, repeated events, and unique (i.e., episodic) events. Behavioral results showed equivalent reaction times in all 4 conditions. True sentences were verified faster than false sentences, except for unique events for which no significant difference was observed. Electrophysiological results showed that the N400 (which is classically associated with retrieval from semantic memory) was maximal for general facts and the LPC (which is classically associated with retrieval from episodic memory) was maximal for unique events. For both ERP components, the two personal semantic conditions (i.e., autobiographical facts and repeated events) systematically differed from semantic memory. In addition, N400 amplitudes also differentiated autobiographical facts from unique events. Autobiographical facts and repeated events did not differ significantly from each other but their corresponding scalp distributions differed from those associated with general facts. Our results suggest that the neural correlates of personal semantics can be distinguished from those of semantic and episodic memory, and may provide clues as to how unique events are transformed to semantic memory. Copyright © 2015 Elsevier Ltd. All rights reserved.
ERIC Educational Resources Information Center
Cremer, M.; Schoonen, R.
2013-01-01
The influences of word decoding, availability, and accessibility of semantic word knowledge on reading comprehension were investigated for monolingual "("n = 65) and bilingual children ("n" = 70). Despite equal decoding abilities, monolingual children outperformed bilingual children with regard to reading comprehension and…
NPI Licensing and Beyond: Children's Knowledge of the Semantics of "Any"
ERIC Educational Resources Information Center
Tieu, Lyn; Lidz, Jeffrey
2016-01-01
This article presents a study of preschool-aged children's knowledge of the semantics of the negative polarity item (NPI) "any". NPIs like "any" differ in distribution from non-polarity-sensitive indefinites like "a": "Any" is restricted to downward-entailing linguistic environments (Fauconnier 1975, 1979;…
Visual imagery processing and knowledge of famous names in Alzheimer's disease and MCI.
Borg, Céline; Thomas-Antérion, Catherine; Bogey, Soline; Davier, Karine; Laurent, Bernard
2010-09-01
The study of memory for famous people and visual imagery retrieval was investigated in patients in the early stages of Alzheimer's disease (AD) and in the prodromal stage of AD, so-called Mild Cognitive Impairment (MCI). Fifteen patients with AD (MMSE > or = 23), 15 patients with amnestic MCI (a-MCI) and 15 normal controls (NC) performed a famous names test designed to evaluate the semantic and distinctive physical features knowledge of famous persons. Results indicated that patients with AD and a-MCI generated significantly less physical features and semantic biographical knowledge about famous persons than did normal control participants. Additionally, significant differences were observed between a-MCI and AD patients in all tasks. The present findings confirm recent studies reporting semantic memory impairment in MCI. Moreover, the current findings show that mental imagery is lowered in a-MCI and AD and is likely related to the early semantic impairment.
Ziaimatin, Hasti; Groza, Tudor; Tudorache, Tania; Hunter, Jane
2016-12-01
Collaboration platforms provide a dynamic environment where the content is subject to ongoing evolution through expert contributions. The knowledge embedded in such platforms is not static as it evolves through incremental refinements - or micro-contributions. Such refinements provide vast resources of tacit knowledge and experience. In our previous work, we proposed and evaluated a Semantic and Time-dependent Expertise Profiling (STEP) approach for capturing expertise from micro-contributions. In this paper we extend our investigation to structured micro-contributions that emerge from an ontology engineering environment, such as the one built for developing the International Classification of Diseases (ICD) revision 11. We take advantage of the semantically related nature of these structured micro-contributions to showcase two major aspects: (i) a novel semantic similarity metric, in addition to an approach for creating bottom-up baseline expertise profiles using expertise centroids; and (ii) the application of STEP in this new environment combined with the use of the same semantic similarity measure to both compare STEP against baseline profiles, as well as to investigate the coverage of these baseline profiles by STEP.
Borovsky, Arielle; Ellis, Erica M; Evans, Julia L; Elman, Jeffrey L
2016-11-01
Although the size of a child's vocabulary associates with language-processing skills, little is understood regarding how this relation emerges. This investigation asks whether and how the structure of vocabulary knowledge affects language processing in English-learning 24-month-old children (N = 32; 18 F, 14 M). Parental vocabulary report was used to calculate semantic density in several early-acquired semantic categories. Performance on two language-processing tasks (lexical recognition and sentence processing) was compared as a function of semantic density. In both tasks, real-time comprehension was facilitated for higher density items, whereas lower density items experienced more interference. The findings indicate that language-processing skills develop heterogeneously and are influenced by the semantic network surrounding a known word. © 2016 The Authors. Child Development © 2016 Society for Research in Child Development, Inc.
A Semantic Web-based System for Managing Clinical Archetypes.
Fernandez-Breis, Jesualdo Tomas; Menarguez-Tortosa, Marcos; Martinez-Costa, Catalina; Fernandez-Breis, Eneko; Herrero-Sempere, Jose; Moner, David; Sanchez, Jesus; Valencia-Garcia, Rafael; Robles, Montserrat
2008-01-01
Archetypes facilitate the sharing of clinical knowledge and therefore are a basic tool for achieving interoperability between healthcare information systems. In this paper, a Semantic Web System for Managing Archetypes is presented. This system allows for the semantic annotation of archetypes, as well for performing semantic searches. The current system is capable of working with both ISO13606 and OpenEHR archetypes.
Abnormal semantic knowledge in a case of developmental amnesia.
Blumenthal, Anna; Duke, Devin; Bowles, Ben; Gilboa, Asaf; Rosenbaum, R Shayna; Köhler, Stefan; McRae, Ken
2017-07-28
An important theory holds that semantic knowledge can develop independently of episodic memory. One strong source of evidence supporting this independence comes from the observation that individuals with early hippocampal damage leading to developmental amnesia generally perform normally on standard tests of semantic memory, despite their profound impairment in episodic memory. However, one aspect of semantic memory that has not been explored is conceptual structure. We built on the theoretically important distinction between intrinsic features of object concepts (e.g., shape, colour, parts) and extrinsic features (e.g., how something is used, where it is typically located). The accrual of extrinsic feature knowledge that is important for concepts such as chair or spoon may depend on binding mechanisms in the hippocampus. We tested HC, an individual with developmental amnesia due to a well-characterized lesion of the hippocampus, on her ability to generate semantic features for object concepts. HC generated fewer extrinsic features than controls, but a similar number of intrinsic features than controls. We also tested her on typicality ratings. Her typicality ratings were abnormal for nonliving things (which more strongly depend on extrinsic features), but normal for living things (which more strongly depend on intrinsic features). In contrast, NB, who has MTL but not hippocampal damage due to surgery, showed no impairments in either task. These results suggest that episodic and semantic memory are not entirely independent, and that the hippocampus is important for learning some aspects of conceptual knowledge. Copyright © 2017 Elsevier Ltd. All rights reserved.
Savill, Nicola; Ellis, Andrew W; Jefferies, Elizabeth
2017-04-01
Verbal short-term memory (STM) is a crucial cognitive function central to language learning, comprehension and reasoning, yet the processes that underlie this capacity are not fully understood. In particular, although STM primarily draws on a phonological code, interactions between long-term phonological and semantic representations might help to stabilise the phonological trace for words ("semantic binding hypothesis"). This idea was first proposed to explain the frequent phoneme recombination errors made by patients with semantic dementia when recalling words that are no longer fully understood. However, converging evidence in support of semantic binding is scant: it is unusual for studies of healthy participants to examine serial recall at the phoneme level and also it is difficult to separate the contribution of phonological-lexical knowledge from effects of word meaning. We used a new method to disentangle these influences in healthy individuals by training new 'words' with or without associated semantic information. We examined phonological coherence in immediate serial recall (ISR), both immediately and the day after training. Trained items were more likely to be recalled than novel nonwords, confirming the importance of phonological-lexical knowledge, and items with semantic associations were also produced more accurately than those with no meaning, at both time points. For semantically-trained items, there were fewer phoneme ordering and identity errors, and consequently more complete target items were produced in both correct and incorrect list positions. These data show that lexical-semantic knowledge improves the robustness of verbal STM at the sub-item level, even when the effect of phonological familiarity is taken into account. Copyright © 2016 Elsevier Ltd. All rights reserved.
Knowledge Representation Issues in Semantic Graphs for Relationship Detection
DOE Office of Scientific and Technical Information (OSTI.GOV)
Barthelemy, M; Chow, E; Eliassi-Rad, T
2005-02-02
An important task for Homeland Security is the prediction of threat vulnerabilities, such as through the detection of relationships between seemingly disjoint entities. A structure used for this task is a ''semantic graph'', also known as a ''relational data graph'' or an ''attributed relational graph''. These graphs encode relationships as typed links between a pair of typed nodes. Indeed, semantic graphs are very similar to semantic networks used in AI. The node and link types are related through an ontology graph (also known as a schema). Furthermore, each node has a set of attributes associated with it (e.g., ''age'' maymore » be an attribute of a node of type ''person''). Unfortunately, the selection of types and attributes for both nodes and links depends on human expertise and is somewhat subjective and even arbitrary. This subjectiveness introduces biases into any algorithm that operates on semantic graphs. Here, we raise some knowledge representation issues for semantic graphs and provide some possible solutions using recently developed ideas in the field of complex networks. In particular, we use the concept of transitivity to evaluate the relevance of individual links in the semantic graph for detecting relationships. We also propose new statistical measures for semantic graphs and illustrate these semantic measures on graphs constructed from movies and terrorism data.« less
Wu, Zhenyu; Xu, Yuan; Yang, Yunong; Zhang, Chunhong; Zhu, Xinning; Ji, Yang
2017-02-20
Web of Things (WoT) facilitates the discovery and interoperability of Internet of Things (IoT) devices in a cyber-physical system (CPS). Moreover, a uniform knowledge representation of physical resources is quite necessary for further composition, collaboration, and decision-making process in CPS. Though several efforts have integrated semantics with WoT, such as knowledge engineering methods based on semantic sensor networks (SSN), it still could not represent the complex relationships between devices when dynamic composition and collaboration occur, and it totally depends on manual construction of a knowledge base with low scalability. In this paper, to addresses these limitations, we propose the semantic Web of Things (SWoT) framework for CPS (SWoT4CPS). SWoT4CPS provides a hybrid solution with both ontological engineering methods by extending SSN and machine learning methods based on an entity linking (EL) model. To testify to the feasibility and performance, we demonstrate the framework by implementing a temperature anomaly diagnosis and automatic control use case in a building automation system. Evaluation results on the EL method show that linking domain knowledge to DBpedia has a relative high accuracy and the time complexity is at a tolerant level. Advantages and disadvantages of SWoT4CPS with future work are also discussed.
Semantic e-Learning: Next Generation of e-Learning?
NASA Astrophysics Data System (ADS)
Konstantinos, Markellos; Penelope, Markellou; Giannis, Koutsonikos; Aglaia, Liopa-Tsakalidi
Semantic e-learning aspires to be the next generation of e-learning, since the understanding of learning materials and knowledge semantics allows their advanced representation, manipulation, sharing, exchange and reuse and ultimately promote efficient online experiences for users. In this context, the paper firstly explores some fundamental Semantic Web technologies and then discusses current and potential applications of these technologies in e-learning domain, namely, Semantic portals, Semantic search, personalization, recommendation systems, social software and Web 2.0 tools. Finally, it highlights future research directions and open issues of the field.
Extracting Useful Semantic Information from Large Scale Corpora of Text
ERIC Educational Resources Information Center
Mendoza, Ray Padilla, Jr.
2012-01-01
Extracting and representing semantic information from large scale corpora is at the crux of computer-assisted knowledge generation. Semantic information depends on collocation extraction methods, mathematical models used to represent distributional information, and weighting functions which transform the space. This dissertation provides a…
Yoo, Min-Jung; Grozel, Clément; Kiritsis, Dimitris
2016-07-08
This paper describes our conceptual framework of closed-loop lifecycle information sharing for product-service in the Internet of Things (IoT). The framework is based on the ontology model of product-service and a type of IoT message standard, Open Messaging Interface (O-MI) and Open Data Format (O-DF), which ensures data communication. (1) BACKGROUND: Based on an existing product lifecycle management (PLM) methodology, we enhanced the ontology model for the purpose of integrating efficiently the product-service ontology model that was newly developed; (2) METHODS: The IoT message transfer layer is vertically integrated into a semantic knowledge framework inside which a Semantic Info-Node Agent (SINA) uses the message format as a common protocol of product-service lifecycle data transfer; (3) RESULTS: The product-service ontology model facilitates information retrieval and knowledge extraction during the product lifecycle, while making more information available for the sake of service business creation. The vertical integration of IoT message transfer, encompassing all semantic layers, helps achieve a more flexible and modular approach to knowledge sharing in an IoT environment; (4) Contribution: A semantic data annotation applied to IoT can contribute to enhancing collected data types, which entails a richer knowledge extraction. The ontology-based PLM model enables as well the horizontal integration of heterogeneous PLM data while breaking traditional vertical information silos; (5) CONCLUSION: The framework was applied to a fictive case study with an electric car service for the purpose of demonstration. For the purpose of demonstrating the feasibility of the approach, the semantic model is implemented in Sesame APIs, which play the role of an Internet-connected Resource Description Framework (RDF) database.
Yoo, Min-Jung; Grozel, Clément; Kiritsis, Dimitris
2016-01-01
This paper describes our conceptual framework of closed-loop lifecycle information sharing for product-service in the Internet of Things (IoT). The framework is based on the ontology model of product-service and a type of IoT message standard, Open Messaging Interface (O-MI) and Open Data Format (O-DF), which ensures data communication. (1) Background: Based on an existing product lifecycle management (PLM) methodology, we enhanced the ontology model for the purpose of integrating efficiently the product-service ontology model that was newly developed; (2) Methods: The IoT message transfer layer is vertically integrated into a semantic knowledge framework inside which a Semantic Info-Node Agent (SINA) uses the message format as a common protocol of product-service lifecycle data transfer; (3) Results: The product-service ontology model facilitates information retrieval and knowledge extraction during the product lifecycle, while making more information available for the sake of service business creation. The vertical integration of IoT message transfer, encompassing all semantic layers, helps achieve a more flexible and modular approach to knowledge sharing in an IoT environment; (4) Contribution: A semantic data annotation applied to IoT can contribute to enhancing collected data types, which entails a richer knowledge extraction. The ontology-based PLM model enables as well the horizontal integration of heterogeneous PLM data while breaking traditional vertical information silos; (5) Conclusion: The framework was applied to a fictive case study with an electric car service for the purpose of demonstration. For the purpose of demonstrating the feasibility of the approach, the semantic model is implemented in Sesame APIs, which play the role of an Internet-connected Resource Description Framework (RDF) database. PMID:27399717
Comprehension of concrete and abstract words in semantic dementia
Jefferies, Elizabeth; Patterson, Karalyn; Jones, Roy W.; Lambon Ralph, Matthew A.
2009-01-01
The vast majority of brain-injured patients with semantic impairment have better comprehension of concrete than abstract words. In contrast, several patients with semantic dementia (SD), who show circumscribed atrophy of the anterior temporal lobes bilaterally, have been reported to show reverse imageability effects, i.e., relative preservation of abstract knowledge. Although these reports largely concern individual patients, some researchers have recently proposed that superior comprehension of abstract concepts is a characteristic feature of SD. This would imply that the anterior temporal lobes are particularly crucial for processing sensory aspects of semantic knowledge, which are associated with concrete not abstract concepts. However, functional neuroimaging studies of healthy participants do not unequivocally predict reverse imageability effects in SD because the temporal poles sometimes show greater activation for more abstract concepts. We examined a case-series of eleven SD patients on a synonym judgement test that orthogonally varied the frequency and imageability of the items. All patients had higher success rates for more imageable as well as more frequent words, suggesting that (a) the anterior temporal lobes underpin semantic knowledge for both concrete and abstract concepts, (b) more imageable items – perhaps due to their richer multimodal representations – are typically more robust in the face of global semantic degradation and (c) reverse imageability effects are not a characteristic feature of SD. PMID:19586212
Integrated Japanese Dependency Analysis Using a Dialog Context
NASA Astrophysics Data System (ADS)
Ikegaya, Yuki; Noguchi, Yasuhiro; Kogure, Satoru; Itoh, Toshihiko; Konishi, Tatsuhiro; Kondo, Makoto; Asoh, Hideki; Takagi, Akira; Itoh, Yukihiro
This paper describes how to perform syntactic parsing and semantic analysis in a dialog system. The paper especially deals with how to disambiguate potentially ambiguous sentences using the contextual information. Although syntactic parsing and semantic analysis are often studied independently of each other, correct parsing of a sentence often requires the semantic information on the input and/or the contextual information prior to the input. Accordingly, we merge syntactic parsing with semantic analysis, which enables syntactic parsing taking advantage of the semantic content of an input and its context. One of the biggest problems of semantic analysis is how to interpret dependency structures. We employ a framework for semantic representations that circumvents the problem. Within the framework, the meaning of any predicate is converted into a semantic representation which only permits a single type of predicate: an identifying predicate "aru". The semantic representations are expressed as sets of "attribute-value" pairs, and those semantic representations are stored in the context information. Our system disambiguates syntactic/semantic ambiguities of inputs referring to the attribute-value pairs in the context information. We have experimentally confirmed the effectiveness of our approach; specifically, the experiment confirmed high accuracy of parsing and correctness of generated semantic representations.
Modeling and formal representation of geospatial knowledge for the Geospatial Semantic Web
NASA Astrophysics Data System (ADS)
Huang, Hong; Gong, Jianya
2008-12-01
GML can only achieve geospatial interoperation at syntactic level. However, it is necessary to resolve difference of spatial cognition in the first place in most occasions, so ontology was introduced to describe geospatial information and services. But it is obviously difficult and improper to let users to find, match and compose services, especially in some occasions there are complicated business logics. Currently, with the gradual introduction of Semantic Web technology (e.g., OWL, SWRL), the focus of the interoperation of geospatial information has shifted from syntactic level to Semantic and even automatic, intelligent level. In this way, Geospatial Semantic Web (GSM) can be put forward as an augmentation to the Semantic Web that additionally includes geospatial abstractions as well as related reasoning, representation and query mechanisms. To advance the implementation of GSM, we first attempt to construct the mechanism of modeling and formal representation of geospatial knowledge, which are also two mostly foundational phases in knowledge engineering (KE). Our attitude in this paper is quite pragmatical: we argue that geospatial context is a formal model of the discriminate environment characters of geospatial knowledge, and the derivation, understanding and using of geospatial knowledge are located in geospatial context. Therefore, first, we put forward a primitive hierarchy of geospatial knowledge referencing first order logic, formal ontologies, rules and GML. Second, a metamodel of geospatial context is proposed and we use the modeling methods and representation languages of formal ontologies to process geospatial context. Thirdly, we extend Web Process Service (WPS) to be compatible with local DLL for geoprocessing and possess inference capability based on OWL.
Dao, Tien Tuan; Hoang, Tuan Nha; Ta, Xuan Hien; Tho, Marie Christine Ho Ba
2013-02-01
Human musculoskeletal system resources of the human body are valuable for the learning and medical purposes. Internet-based information from conventional search engines such as Google or Yahoo cannot response to the need of useful, accurate, reliable and good-quality human musculoskeletal resources related to medical processes, pathological knowledge and practical expertise. In this present work, an advanced knowledge-based personalized search engine was developed. Our search engine was based on a client-server multi-layer multi-agent architecture and the principle of semantic web services to acquire dynamically accurate and reliable HMSR information by a semantic processing and visualization approach. A security-enhanced mechanism was applied to protect the medical information. A multi-agent crawler was implemented to develop a content-based database of HMSR information. A new semantic-based PageRank score with related mathematical formulas were also defined and implemented. As the results, semantic web service descriptions were presented in OWL, WSDL and OWL-S formats. Operational scenarios with related web-based interfaces for personal computers and mobile devices were presented and analyzed. Functional comparison between our knowledge-based search engine, a conventional search engine and a semantic search engine showed the originality and the robustness of our knowledge-based personalized search engine. In fact, our knowledge-based personalized search engine allows different users such as orthopedic patient and experts or healthcare system managers or medical students to access remotely into useful, accurate, reliable and good-quality HMSR information for their learning and medical purposes. Copyright © 2012 Elsevier Inc. All rights reserved.
Formalization of treatment guidelines using Fuzzy Cognitive Maps and semantic web tools.
Papageorgiou, Elpiniki I; Roo, Jos De; Huszka, Csaba; Colaert, Dirk
2012-02-01
Therapy decision making and support in medicine deals with uncertainty and needs to take into account the patient's clinical parameters, the context of illness and the medical knowledge of the physician and guidelines to recommend a treatment therapy. This research study is focused on the formalization of medical knowledge using a cognitive process, called Fuzzy Cognitive Maps (FCMs) and semantic web approach. The FCM technique is capable of dealing with situations including uncertain descriptions using similar procedure such as human reasoning does. Thus, it was selected for the case of modeling and knowledge integration of clinical practice guidelines. The semantic web tools were established to implement the FCM approach. The knowledge base was constructed from the clinical guidelines as the form of if-then fuzzy rules. These fuzzy rules were transferred to FCM modeling technique and, through the semantic web tools, the whole formalization was accomplished. The problem of urinary tract infection (UTI) in adult community was examined for the proposed approach. Forty-seven clinical concepts and eight therapy concepts were identified for the antibiotic treatment therapy problem of UTIs. A preliminary pilot-evaluation study with 55 patient cases showed interesting findings; 91% of the antibiotic treatments proposed by the implemented approach were in fully agreement with the guidelines and physicians' opinions. The results have shown that the suggested approach formalizes medical knowledge efficiently and gives a front-end decision on antibiotics' suggestion for cystitis. Concluding, modeling medical knowledge/therapeutic guidelines using cognitive methods and web semantic tools is both reliable and useful. Copyright © 2011 Elsevier Inc. All rights reserved.
Relation Extraction with Weak Supervision and Distributional Semantics
2013-05-01
DATES COVERED 00-00-2013 to 00-00-2013 4 . TITLE AND SUBTITLE Relation Extraction with Weak Supervision and Distributional Semantics 5a...ix List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x 1 Introduction 1 2 Prior Work 4 ...2.1 Supervised relation extraction . . . . . . . . . . . . . . . . . . . . . 4 2.2 Distant supervision for relation extraction
Phonological Priming and Cohort Effects in Toddlers
ERIC Educational Resources Information Center
Mani, Nivedita; Plunkett, Kim
2011-01-01
Adult word recognition is influenced by prior exposure to phonologically or semantically related words ("cup" primes "cat" or "plate") compared to unrelated words ("door"), suggesting that words are organised in the adult lexicon based on their phonological and semantic properties and that word recognition implicates not just the heard word, but…
ERIC Educational Resources Information Center
Connor, Carol McDonald; Day, Stephanie L.; Phillips, Beth; Sparapani, Nicole; Ingebrand, Sarah W.; McLean, Leigh; Barrus, Angela; Kaschak, Michael P.
2016-01-01
Many assume that cognitive and linguistic processes, such as semantic knowledge (SK) and self-regulation (SR), subserve learned skills like reading. However, complex models of interacting and bootstrapping effects of SK, SR, instruction, and reading hypothesize reciprocal effects. Testing this "lattice" model with children (n = 852)…
Availability of Semantic Knowledge in Familiar-Only Experiences for Names
ERIC Educational Resources Information Center
Bowles, Ben; Köhler, Stefan
2014-01-01
Situations in which the name of a person is perceived as familiar but does not trigger recall of pertinent semantic knowledge are common in daily life. In current connectionist models of person recognition, such "familiar-only" experiences reflect supra-threshold activation at person-identity nodes but subthreshold activation at nodes…
Resourcing Teachers to Tide the Semantic Wave to Whole School Literacy Development
ERIC Educational Resources Information Center
Humphrey, S.; Robinson, S.
2012-01-01
In this paper we report on a whole school literacy research project, Embedding Literacies in the KLA's (ELK). The starting point for this endeavour is the theory of knowledge development conceptualised within the sociology of education as the semantic wave (Maton, forthcoming). As discipline knowledge typically resides in the "high…
Computer-Based Semantic Network in Molecular Biology: A Demonstration.
ERIC Educational Resources Information Center
Callman, Joshua L.; And Others
This paper analyzes the hardware and software features that would be desirable in a computer-based semantic network system for representing biology knowledge. It then describes in detail a prototype network of molecular biology knowledge that has been developed using Filevision software and a Macintosh computer. The prototype contains about 100…
A Metadata based Knowledge Discovery Methodology for Seeding Translational Research.
Kothari, Cartik R; Payne, Philip R O
2015-01-01
In this paper, we present a semantic, metadata based knowledge discovery methodology for identifying teams of researchers from diverse backgrounds who can collaborate on interdisciplinary research projects: projects in areas that have been identified as high-impact areas at The Ohio State University. This methodology involves the semantic annotation of keywords and the postulation of semantic metrics to improve the efficiency of the path exploration algorithm as well as to rank the results. Results indicate that our methodology can discover groups of experts from diverse areas who can collaborate on translational research projects.
Semantic Convergence in the Bilingual Lexicon
ERIC Educational Resources Information Center
Ameel, Eef; Malt, Barbara C.; Storms, Gert; Van Assche, Fons
2009-01-01
Bilinguals' lexical mappings for their two languages have been found to converge toward a common naming pattern. The present paper investigates in more detail how semantic convergence is manifested in bilingual lexical knowledge. We examined how semantic convergence affects the centers and boundaries of lexical categories for common household…
Peters, Frédéric; Majerus, Steve; De Baerdemaeker, Julie; Salmon, Eric; Collette, Fabienne
2009-12-01
A decrease in verbal short-term memory (STM) capacity is consistently observed in patients with Alzheimer's disease (AD). Although this impairment has been mainly attributed to attentional deficits during encoding and maintenance, the progressive deterioration of semantic knowledge in early stages of AD may also be an important determinant of poor STM performance. The aim of this study was to examine the influence of semantic knowledge on verbal short-term memory storage capacity in normal aging and in AD by exploring the impact of word imageability on STM performance. Sixteen patients suffering from mild AD, 16 healthy elderly subjects and 16 young subjects performed an immediate serial recall task using word lists containing high or low imageability words. All participant groups recalled more high imageability words than low imageability words, but the effect of word imageability on verbal STM was greater in AD patients than in both the young and the elderly control groups. More precisely, AD patients showed a marked decrease in STM performance when presented with lists of low imageability words, whereas recall of high imageability words was relatively well preserved. Furthermore, AD patients displayed an abnormal proportion of phonological errors in the low imageability condition. Overall, these results indicate that the support of semantic knowledge on STM performance was impaired for lists of low imageability words in AD patients. More generally, these findings suggest that the deterioration of semantic knowledge is partly responsible for the poor verbal short-term storage capacity observed in AD.
The semantic organisation of proper nouns: the case of people and brand names.
Crutch, Sebastian J; Warrington, Elizabeth K
2004-01-01
We describe the performance of a patient (AZ) with a semantic refractory access disorder on a series of experiments probing comprehension of two broad proper noun categories, namely person names and brand names. By inducing and manipulating the semantic relatedness effects which are commonly observed in semantic refractory access patients, we demonstrate that famous person knowledge is primarily organised by occupation, whilst knowledge of brands is organised by product type. For instance, we show that AZ has significantly greater difficulty identifying a famous person from among distractor personalities who have the same occupation (e.g. composers: Beethoven, Mozart, Handel, and Bach) than those who have different occupations (e.g. Beethoven, Picasso, Shakespeare, and Jefferson). We also show that such semantic relatedness effects do not occur when stimuli are grouped by another variable such as nationality. We argue that these semantic distance effects reflect the greater build-up of refractoriness among concepts which are supported by shared neural circuitry. In psychological space, it seems natural that these individuals should be classified in this way. The strength of our findings lie in the fact that this organisation of psychological space is mirrored by neural organisation. Thus, we report a previously undocumented degree of fine-grain organisation within conceptual knowledge of these classes of proper nouns. We also interpret our data as providing the strongest empirical support to date for the semantic module of cognitive models of person recognition.
Personal semantic memory: insights from neuropsychological research on amnesia.
Grilli, Matthew D; Verfaellie, Mieke
2014-08-01
This paper provides insight into the cognitive and neural mechanisms of personal semantic memory, knowledge that is specific and unique to individuals, by reviewing neuropsychological research on stable amnesia secondary to medial temporal lobe damage. The results reveal that personal semantic memory does not depend on a unitary set of cognitive and neural mechanisms. Findings show that autobiographical fact knowledge reflects an experience-near type of personal semantic memory that relies on the medial temporal lobe for retrieval, albeit less so than personal episodic memory. Additional evidence demonstrates that new autobiographical fact learning likely relies on the medial temporal lobe, but the extent to which remains unclear. Other findings show that retrieval of personal traits/roles and new learning of personal traits/roles and thoughts/beliefs are independent of the medial temporal lobe and thus may represent highly conceptual types of personal semantic memory that are stored in the neocortex. Published by Elsevier Ltd.
[Knowing without remembering: the contribution of developmental amnesia].
Lebrun-Givois, C; Guillery-Girard, B; Thomas-Anterion, C; Laurent, B
2008-05-01
The organization of episodic and semantic memory is currently debated, and especially the rule of the hippocampus in the functioning of these two systems. Since theories derived from the observation of the famous patient HM, that highlighted the involvement of this structure in these two systems, numerous studies questioned the implication of the hippocampus in learning a new semantic knowledge. Among these studies, we found Vargha-Kadem's cases of developmental amnesia. In spite of their clear hippocampal atrophy and a massive impairment of episodic memory, these children were able to acquire de novo new semantic knowledge. In the present paper, we describe a new case of developmental amnesia characteristic of this syndrome. In conclusion, the whole published data question the implication of the hippocampus in every semantic learning and suggest the existence of a neocortical network, slower and that needs more exposures to semantic stimuli than the hippocampal one, which can supply a massive hippocampal impairment.
Actively learning human gaze shifting paths for semantics-aware photo cropping.
Zhang, Luming; Gao, Yue; Ji, Rongrong; Xia, Yingjie; Dai, Qionghai; Li, Xuelong
2014-05-01
Photo cropping is a widely used tool in printing industry, photography, and cinematography. Conventional cropping models suffer from the following three challenges. First, the deemphasized role of semantic contents that are many times more important than low-level features in photo aesthetics. Second, the absence of a sequential ordering in the existing models. In contrast, humans look at semantically important regions sequentially when viewing a photo. Third, the difficulty of leveraging inputs from multiple users. Experience from multiple users is particularly critical in cropping as photo assessment is quite a subjective task. To address these challenges, this paper proposes semantics-aware photo cropping, which crops a photo by simulating the process of humans sequentially perceiving semantically important regions of a photo. We first project the local features (graphlets in this paper) onto the semantic space, which is constructed based on the category information of the training photos. An efficient learning algorithm is then derived to sequentially select semantically representative graphlets of a photo, and the selecting process can be interpreted by a path, which simulates humans actively perceiving semantics in a photo. Furthermore, we learn a prior distribution of such active graphlet paths from training photos that are marked as aesthetically pleasing by multiple users. The learned priors enforce the corresponding active graphlet path of a test photo to be maximally similar to those from the training photos. Experimental results show that: 1) the active graphlet path accurately predicts human gaze shifting, and thus is more indicative for photo aesthetics than conventional saliency maps and 2) the cropped photos produced by our approach outperform its competitors in both qualitative and quantitative comparisons.
Semantic framework for mapping object-oriented model to semantic web languages
Ježek, Petr; Mouček, Roman
2015-01-01
The article deals with and discusses two main approaches in building semantic structures for electrophysiological metadata. It is the use of conventional data structures, repositories, and programming languages on one hand and the use of formal representations of ontologies, known from knowledge representation, such as description logics or semantic web languages on the other hand. Although knowledge engineering offers languages supporting richer semantic means of expression and technological advanced approaches, conventional data structures and repositories are still popular among developers, administrators and users because of their simplicity, overall intelligibility, and lower demands on technical equipment. The choice of conventional data resources and repositories, however, raises the question of how and where to add semantics that cannot be naturally expressed using them. As one of the possible solutions, this semantics can be added into the structures of the programming language that accesses and processes the underlying data. To support this idea we introduced a software prototype that enables its users to add semantically richer expressions into a Java object-oriented code. This approach does not burden users with additional demands on programming environment since reflective Java annotations were used as an entry for these expressions. Moreover, additional semantics need not to be written by the programmer directly to the code, but it can be collected from non-programmers using a graphic user interface. The mapping that allows the transformation of the semantically enriched Java code into the Semantic Web language OWL was proposed and implemented in a library named the Semantic Framework. This approach was validated by the integration of the Semantic Framework in the EEG/ERP Portal and by the subsequent registration of the EEG/ERP Portal in the Neuroscience Information Framework. PMID:25762923
Semantic framework for mapping object-oriented model to semantic web languages.
Ježek, Petr; Mouček, Roman
2015-01-01
The article deals with and discusses two main approaches in building semantic structures for electrophysiological metadata. It is the use of conventional data structures, repositories, and programming languages on one hand and the use of formal representations of ontologies, known from knowledge representation, such as description logics or semantic web languages on the other hand. Although knowledge engineering offers languages supporting richer semantic means of expression and technological advanced approaches, conventional data structures and repositories are still popular among developers, administrators and users because of their simplicity, overall intelligibility, and lower demands on technical equipment. The choice of conventional data resources and repositories, however, raises the question of how and where to add semantics that cannot be naturally expressed using them. As one of the possible solutions, this semantics can be added into the structures of the programming language that accesses and processes the underlying data. To support this idea we introduced a software prototype that enables its users to add semantically richer expressions into a Java object-oriented code. This approach does not burden users with additional demands on programming environment since reflective Java annotations were used as an entry for these expressions. Moreover, additional semantics need not to be written by the programmer directly to the code, but it can be collected from non-programmers using a graphic user interface. The mapping that allows the transformation of the semantically enriched Java code into the Semantic Web language OWL was proposed and implemented in a library named the Semantic Framework. This approach was validated by the integration of the Semantic Framework in the EEG/ERP Portal and by the subsequent registration of the EEG/ERP Portal in the Neuroscience Information Framework.
Su, Yi Esther; Su, Lin-Yan
2015-07-01
This study investigated the interpretation of the logical words 'some' and 'every…or…' in 4-15-year-old high-functioning Mandarin-speaking children with autism spectrum disorders (ASD). Children with ASD performed similarly to typical controls in demonstrating semantic knowledge of simple sentences with 'some', and they had delayed knowledge of the complex sentences with 'every…or…'. Interestingly, the children with ASD had pragmatic knowledge of the scalar implicatures of these logical words, parallel to those of the typical controls. Taken together, the interpretation of logical words may be a relative strength in children with ASD. It is possible that some aspects of semantics and pragmatics may be selectively spared in ASD, due to the contribution the language faculty makes to language acquisition in the ASD population.
Disentangling Linguistic Modality Effects in Semantic Processing
ERIC Educational Resources Information Center
Moita, Mara; Nunes, Maria Vânia
2017-01-01
Sensory systems are essential for perceiving and conceptualizing our semantic knowledge about the world and the way we interact with it. Despite studies reporting neural changes to compensate for the absence of a given sensory modality, studies focusing on the assessment of semantic processing reveal poor performances by deaf individuals when…
Structure and Deterioration of Semantic Memory: A Neuropsychological and Computational Investigation
ERIC Educational Resources Information Center
Rogers, Timothy T.; Lambon Ralph, Matthew A.; Garrard, Peter; Bozeat, Sasha; McClelland, James L.; Hodges, John R.; Patterson, Karalyn
2004-01-01
Wernicke (1900, as cited in G. H. Eggert, 1977) suggested that semantic knowledge arises from the interaction of perceptual representations of objects and words. The authors present a parallel distributed processing implementation of this theory, in which semantic representations emerge from mechanisms that acquire the mappings between visual…
Knowledge of Natural Kinds in Semantic Dementia and Alzheimer's Disease
ERIC Educational Resources Information Center
Cross, Katy; Smith, Edward E.; Grossman, Murray
2008-01-01
We examined the semantic impairment for natural kinds in patients with probable Alzheimer's disease (AD) and semantic dementia (SD) using an inductive reasoning paradigm. To learn about the relationships between natural kind exemplars and how these are distinguished from manufactured artifacts, subjects judged the strength of arguments such as…
Personal Experience and Arithmetic Meaning in Semantic Dementia
ERIC Educational Resources Information Center
Julien, Camille L.; Neary, David; Snowden, Julie S.
2010-01-01
Arithmetic skills are generally claimed to be preserved in semantic dementia (SD), suggesting functional independence of arithmetic knowledge from other aspects of semantic memory. However, in a recent case series analysis we showed that arithmetic performance in SD is not entirely normal. The finding of a direct association between severity of…
The Role of Semantic Features in Verb Processing
ERIC Educational Resources Information Center
Bonnotte, Isabelle
2008-01-01
The present study examined the general hypothesis that, as for nouns, stable representations of semantic knowledge relative to situations expressed by verbs are available and accessible in long term memory in normal people. Regular associations between verbs and past tenses in French adults allowed to abstract two superordinate semantic features…
Oxytocin Modulates Semantic Integration in Speech Comprehension.
Ye, Zheng; Stolk, Arjen; Toni, Ivan; Hagoort, Peter
2017-02-01
Listeners interpret utterances by integrating information from multiple sources including word level semantics and world knowledge. When the semantics of an expression is inconsistent with their knowledge about the world, the listener may have to search through the conceptual space for alternative possible world scenarios that can make the expression more acceptable. Such cognitive exploration requires considerable computational resources and might depend on motivational factors. This study explores whether and how oxytocin, a neuropeptide known to influence social motivation by reducing social anxiety and enhancing affiliative tendencies, can modulate the integration of world knowledge and sentence meanings. The study used a between-participant double-blind randomized placebo-controlled design. Semantic integration, indexed with magnetoencephalography through the N400m marker, was quantified while 45 healthy male participants listened to sentences that were either congruent or incongruent with facts of the world, after receiving intranasally delivered oxytocin or placebo. Compared with congruent sentences, world knowledge incongruent sentences elicited a stronger N400m signal from the left inferior frontal and anterior temporal regions and medial pFC (the N400m effect) in the placebo group. Oxytocin administration significantly attenuated the N400m effect at both sensor and cortical source levels throughout the experiment, in a state-like manner. Additional electrophysiological markers suggest that the absence of the N400m effect in the oxytocin group is unlikely due to the lack of early sensory or semantic processing or a general downregulation of attention. These findings suggest that oxytocin drives listeners to resolve challenges of semantic integration, possibly by promoting the cognitive exploration of alternative possible world scenarios.
NASA Astrophysics Data System (ADS)
van Elk, Michiel; van Schie, Hein; Bekkering, Harold
2014-06-01
Our capacity to use tools and objects is often considered one of the hallmarks of the human species. Many objects greatly extend our bodily capabilities to act in the physical world, such as when using a hammer or a saw. In addition, humans have the remarkable capability to use objects in a flexible fashion and to combine multiple objects in complex actions. We prepare coffee, cook dinner and drive our car. In this review we propose that humans have developed declarative and procedural knowledge, i.e. action semantics that enables us to use objects in a meaningful way. A state-of-the-art review of research on object use is provided, involving behavioral, developmental, neuropsychological and neuroimaging studies. We show that research in each of these domains is characterized by similar discussions regarding (1) the role of object affordances, (2) the relation between goals and means in object use and (3) the functional and neural organization of action semantics. We propose a novel conceptual framework of action semantics to address these issues and to integrate the previous findings. We argue that action semantics entails both multimodal object representations and modality-specific sub-systems, involving manipulation knowledge, functional knowledge and representations of the sensory and proprioceptive consequences of object use. Furthermore, we argue that action semantics are hierarchically organized and selectively activated and used depending on the action intention of the actor and the current task context. Our framework presents an integrative account of multiple findings and perspectives on object use that may guide future studies in this interdisciplinary domain.
Semantic annotation in biomedicine: the current landscape.
Jovanović, Jelena; Bagheri, Ebrahim
2017-09-22
The abundance and unstructured nature of biomedical texts, be it clinical or research content, impose significant challenges for the effective and efficient use of information and knowledge stored in such texts. Annotation of biomedical documents with machine intelligible semantics facilitates advanced, semantics-based text management, curation, indexing, and search. This paper focuses on annotation of biomedical entity mentions with concepts from relevant biomedical knowledge bases such as UMLS. As a result, the meaning of those mentions is unambiguously and explicitly defined, and thus made readily available for automated processing. This process is widely known as semantic annotation, and the tools that perform it are known as semantic annotators.Over the last dozen years, the biomedical research community has invested significant efforts in the development of biomedical semantic annotation technology. Aiming to establish grounds for further developments in this area, we review a selected set of state of the art biomedical semantic annotators, focusing particularly on general purpose annotators, that is, semantic annotation tools that can be customized to work with texts from any area of biomedicine. We also examine potential directions for further improvements of today's annotators which could make them even more capable of meeting the needs of real-world applications. To motivate and encourage further developments in this area, along the suggested and/or related directions, we review existing and potential practical applications and benefits of semantic annotators.
Jefferies, Elizabeth; Patterson, Karalyn; Jones, Roy W; Bateman, David; Lambon Ralph, Matthew A
2004-01-01
This study explored possible reasons for the striking difference between digit span and word span in patients with semantic dementia. Immediate serial recall (ISR) of number and non-number words was examined in four patients. For every case, the recall of single-digit numbers was normal whereas the recall of non-number words was impaired relative to controls. This difference extended to multi-digit numbers, and remained even when frequency, imageability, word length, set size and size of semantic category were matched for the numbers and words. The advantage for number words also applied to the patients' reading performance. Previous studies have suggested that semantic memory plays a critical role in verbal short-term memory (STM) and reading: patients with semantic dementia show superior recall and reading of words that are still relatively well known compared to previously known but now semantically degraded words. Additional assessments suggested that this semantic locus was the basis of the patients' category-specific advantage for numbers. Comprehension was considerably better for number than non-number words. Number knowledge may be relatively preserved in semantic dementia because the cortical atrophy underlying the condition typically spares the areas of the parietal lobes thought to be crucial in numerical cognition but involves the inferolateral temporal-lobes known to support general conceptual knowledge.
ERIC Educational Resources Information Center
Peters, Frederic; Majerus, Steve; De Baerdemaeker, Julie; Salmon, Eric; Collette, Fabienne
2009-01-01
A decrease in verbal short-term memory (STM) capacity is consistently observed in patients with Alzheimer's disease (AD). Although this impairment has been mainly attributed to attentional deficits during encoding and maintenance, the progressive deterioration of semantic knowledge in early stages of AD may also be an important determinant of poor…
Semantic Radical Knowledge and Word Recognition in Chinese for Chinese as Foreign Language Learners
ERIC Educational Resources Information Center
Su, Xiaoxiang; Kim, Young-Suk
2014-01-01
In the present study, we examined the relation of knowledge of semantic radicals to students' language proficiency and word reading for adult Chinese-as-a-foreign language students. Ninety-seven college students rated their proficiency in speaking, listening, reading, and writing in Chinese, and were administered measures of receptive and…
What lies beneath: A comparison of reading aloud in pure alexia and semantic dementia
Hoffman, Paul; Roberts, Daniel J.; Ralph, Matthew A. Lambon; Patterson, Karalyn E.
2014-01-01
Exaggerated effects of word length upon reading-aloud performance define pure alexia, but have also been observed in semantic dementia. Some researchers have proposed a reading-specific account, whereby performance in these two disorders reflects the same cause: impaired orthographic processing. In contrast, according to the primary systems view of acquired reading disorders, pure alexia results from a basic visual processing deficit, whereas degraded semantic knowledge undermines reading performance in semantic dementia. To explore the source of reading deficits in these two disorders, we compared the reading performance of 10 pure alexic and 10 semantic dementia patients, matched in terms of overall severity of reading deficit. The results revealed comparable frequency effects on reading accuracy, but weaker effects of regularity in pure alexia than in semantic dementia. Analysis of error types revealed a higher rate of letter-based errors and a lower rate of regularization responses in pure alexia than in semantic dementia. Error responses were most often words in pure alexia but most often nonwords in semantic dementia. Although all patients made some letter substitution errors, these were characterized by visual similarity in pure alexia and phonological similarity in semantic dementia. Overall, the data indicate that the reading deficits in pure alexia and semantic dementia arise from impairments of visual processing and knowledge of word meaning, respectively. The locus and mechanisms of these impairments are placed within the context of current connectionist models of reading. PMID:24702272
Attention to Distinct Goal-relevant Features Differentially Guides Semantic Knowledge Retrieval.
Hanson, Gavin K; Chrysikou, Evangelia G
2017-07-01
A critical aspect of conceptual knowledge is the selective activation of goal-relevant aspects of meaning. Although the contributions of ventrolateral prefrontal and posterior temporal areas to semantic cognition are well established, the precise role of posterior parietal cortex in semantic control remains unknown. Here, we examined whether this region modulates attention to goal-relevant features within semantic memory according to the same principles that determine the salience of task-relevant object properties during visual attention. Using multivoxel pattern analysis, we decoded attentional referents during a semantic judgment task, in which participants matched an object cue to a target according to concrete (i.e., color, shape) or abstract (i.e., function, thematic context) semantic features. The goal-relevant semantic feature participants attended to (e.g., color or shape, function or theme) could be decoded from task-associated cortical activity with above-chance accuracy, a pattern that held for both concrete and abstract semantic features. A Bayesian confusion matrix analysis further identified differential contributions to representing attentional demands toward specific object properties across lateral prefrontal, posterior temporal, and inferior parietal regions, with the dorsolateral pFC supporting distinctions between higher-order properties and the left intraparietal sulcus being the only region supporting distinctions across all semantic features. These results are the first to demonstrate that patterns of neural activity in the parietal cortex are sensitive to which features of a concept are attended to, thus supporting the contributions of posterior parietal cortex to semantic control.
A Semantic Analysis Method for Scientific and Engineering Code
NASA Technical Reports Server (NTRS)
Stewart, Mark E. M.
1998-01-01
This paper develops a procedure to statically analyze aspects of the meaning or semantics of scientific and engineering code. The analysis involves adding semantic declarations to a user's code and parsing this semantic knowledge with the original code using multiple expert parsers. These semantic parsers are designed to recognize formulae in different disciplines including physical and mathematical formulae and geometrical position in a numerical scheme. In practice, a user would submit code with semantic declarations of primitive variables to the analysis procedure, and its semantic parsers would automatically recognize and document some static, semantic concepts and locate some program semantic errors. A prototype implementation of this analysis procedure is demonstrated. Further, the relationship between the fundamental algebraic manipulations of equations and the parsing of expressions is explained. This ability to locate some semantic errors and document semantic concepts in scientific and engineering code should reduce the time, risk, and effort of developing and using these codes.
Groza, Tudor; Tudorache, Tania; Hunter, Jane
2015-01-01
Collaboration platforms provide a dynamic environment where the content is subject to ongoing evolution through expert contributions. The knowledge embedded in such platforms is not static as it evolves through incremental refinements – or micro-contributions. Such refinements provide vast resources of tacit knowledge and experience. In our previous work, we proposed and evaluated a Semantic and Time-dependent Expertise Profiling (STEP) approach for capturing expertise from micro-contributions. In this paper we extend our investigation to structured micro-contributions that emerge from an ontology engineering environment, such as the one built for developing the International Classification of Diseases (ICD) revision 11. We take advantage of the semantically related nature of these structured micro-contributions to showcase two major aspects: (i) a novel semantic similarity metric, in addition to an approach for creating bottom-up baseline expertise profiles using expertise centroids; and (ii) the application of STEP in this new environment combined with the use of the same semantic similarity measure to both compare STEP against baseline profiles, as well as to investigate the coverage of these baseline profiles by STEP. PMID:28077914
Wu, Zhenyu; Xu, Yuan; Yang, Yunong; Zhang, Chunhong; Zhu, Xinning; Ji, Yang
2017-01-01
Web of Things (WoT) facilitates the discovery and interoperability of Internet of Things (IoT) devices in a cyber-physical system (CPS). Moreover, a uniform knowledge representation of physical resources is quite necessary for further composition, collaboration, and decision-making process in CPS. Though several efforts have integrated semantics with WoT, such as knowledge engineering methods based on semantic sensor networks (SSN), it still could not represent the complex relationships between devices when dynamic composition and collaboration occur, and it totally depends on manual construction of a knowledge base with low scalability. In this paper, to addresses these limitations, we propose the semantic Web of Things (SWoT) framework for CPS (SWoT4CPS). SWoT4CPS provides a hybrid solution with both ontological engineering methods by extending SSN and machine learning methods based on an entity linking (EL) model. To testify to the feasibility and performance, we demonstrate the framework by implementing a temperature anomaly diagnosis and automatic control use case in a building automation system. Evaluation results on the EL method show that linking domain knowledge to DBpedia has a relative high accuracy and the time complexity is at a tolerant level. Advantages and disadvantages of SWoT4CPS with future work are also discussed. PMID:28230725
The accessibility of semantic knowledge for odours that can and cannot be named.
Stevenson, Richard J; Mahmut, Mehmet K
2013-01-01
When faces, objects, or voices are encountered, naming lapses can occur, but this does not preclude knowing other specific semantic information about the nameless thing. In the experiments reported here, we examined whether this is also the case for odours, using a procedure based upon the Pyramid and Palm Trees test. In Experiment 1, participants were presented with a target odour, then two pictures, and had to pick the picture semantically associated with the target. In Experiment 2, participants were presented with a target odour, then two test odours, and again had to pick the semantically associated test stimulus. In each experiment, other tests followed, including a parallel verbal-based test, an odour-naming test, and various ratings. Neither experiment found any evidence of specific semantic knowledge about a target odour, unless the target odour name (Experiment 1) or all of the odour names (Experiment 2) were known. Additional tests suggested that these effects were independent of odour familiarity and similarity. We suggest that the absence of specific semantic information in the absence of a name may reflect poor connectivity between olfactory perceptual and semantic memory systems.
Extent and neural basis of semantic memory impairment in mild cognitive impairment.
Barbeau, Emmanuel J; Didic, Mira; Joubert, Sven; Guedj, Eric; Koric, Lejla; Felician, Olivier; Ranjeva, Jean-Philippe; Cozzone, Patrick; Ceccaldi, Mathieu
2012-01-01
An increasing number of studies indicate that semantic memory is impaired in mild cognitive impairment (MCI). However, the extent and the neural basis of this impairment remain unknown. The aim of the present study was: 1) to evaluate whether all or only a subset of semantic domains are impaired in MCI patients; and 2) to assess the neural substrate of the semantic impairment in MCI patients using voxel-based analysis of MR grey matter density and SPECT perfusion. 29 predominantly amnestic MCI patients and 29 matched control subjects participated in this study. All subjects underwent a full neuropsychological assessment, along with a battery of five tests evaluating different domains of semantic memory. A semantic memory composite Z-score was established on the basis of this battery and was correlated with MRI grey matter density and SPECT perfusion measures. MCI patients were found to have significantly impaired performance across all semantic tasks, in addition to their anterograde memory deficit. Moreover, no temporal gradient was found for famous faces or famous public events and knowledge for the most remote decades was also impaired. Neuroimaging analyses revealed correlations between semantic knowledge and perirhinal/entorhinal areas as well as the anterior hippocampus. Therefore, the deficits in the realm of semantic memory in patients with MCI is more widespread than previously thought and related to dysfunction of brain areas beyond the limbic-diencephalic system involved in episodic memory. The severity of the semantic impairment may indicate a decline of semantic memory that began many years before the patients first consulted.
A case of amnesia at an early age.
Brizzolara, Daniela; Casalini, Claudia; Montanaro, Domenico; Posteraro, Federico
2003-01-01
A dissociation between short- and long-term memory (LTM) and between the episodic and the semantic component of LTM is reported in a young girl who became amnesic at the age of 6 after an episode of acute encephalopathy resulting in bilateral frontal, insular, thalamic, ponto-mesencephalic, hippocampal and temporal lesions, as documented by MRI. The girl became amnesic a few months after starting school. A follow-up investigation showed that she was able to learn to read, write and acquire number facts and procedures and to improve her semantic knowledge. Our results show that the features of adult amnesia can also be found in children and that new semantic knowledge can be acquired in spite of an anterograde memory deficit. This dissociation does not agree with theories viewing long-term declarative memory as a unitary process mediated by the hippocampal system, but supports recent hypotheses that the acquisition of semantic knowledge is independent from episodic memory processes, and takes place through spared cortical regions subjacent to the hippocampi (Vargha-Khadem et al., 1997).
Effects of paired-object affordance in search tasks across the adult lifespan.
Wulff, Melanie; Stainton, Alexandra; Rotshtein, Pia
2016-06-01
The study investigated the processes underlying the retrieval of action information about functional object pairs, focusing on the contribution of procedural and semantic knowledge. We further assessed whether the retrieval of action knowledge is affected by task demands and age. The contribution of procedural knowledge was examined by the way objects were selected, specifically whether active objects were selected before passive objects. The contribution of semantic knowledge was examined by manipulating the relation between targets and distracters. A touchscreen-based search task was used testing young, middle-aged, and elderly participants. Participants had to select by touching two targets among distracters using two search tasks. In an explicit action search task, participants had to select two objects which afforded a mutual action (e.g., functional pair: hammer-nail). Implicit affordance perception was tested using a visual color-matching search task; participants had to select two objects with the same colored frame. In both tasks, half of the colored targets also afforded an action. Overall, middle-aged participants performed better than young and elderly participants, specifically in the action task. Across participants in the action task, accuracy was increased when the distracters were semantically unrelated to the functional pair, while the opposite pattern was observed in the color task. This effect was enhanced with increased age. In the action task all participants utilized procedural knowledge, i.e., selected the active object before the passive object. This result supports the dual-route account from vision to action. Semantic knowledge contributed to both the action and the color task, but procedural knowledge associated with the direct route was primarily retrieved when the task was action-relevant. Across the adulthood lifespan, the data show inverted U-shaped effects of age on the retrieval of action knowledge. Age also linearly increased the involvement of the indirect (semantic) route and the integration of information of the direct and the indirect routes in selection processes. Copyright © 2016 Elsevier Inc. All rights reserved.
Don’t Like RDF Reification? Making Statements about Statements Using Singleton Property
Nguyen, Vinh; Bodenreider, Olivier; Sheth, Amit
2015-01-01
Statements about RDF statements, or meta triples, provide additional information about individual triples, such as the source, the occurring time or place, or the certainty. Integrating such meta triples into semantic knowledge bases would enable the querying and reasoning mechanisms to be aware of provenance, time, location, or certainty of triples. However, an efficient RDF representation for such meta knowledge of triples remains challenging. The existing standard reification approach allows such meta knowledge of RDF triples to be expressed using RDF by two steps. The first step is representing the triple by a Statement instance which has subject, predicate, and object indicated separately in three different triples. The second step is creating assertions about that instance as if it is a statement. While reification is simple and intuitive, this approach does not have formal semantics and is not commonly used in practice as described in the RDF Primer. In this paper, we propose a novel approach called Singleton Property for representing statements about statements and provide a formal semantics for it. We explain how this singleton property approach fits well with the existing syntax and formal semantics of RDF, and the syntax of SPARQL query language. We also demonstrate the use of singleton property in the representation and querying of meta knowledge in two examples of Semantic Web knowledge bases: YAGO2 and BKR. Our experiments on the BKR show that the singleton property approach gives a decent performance in terms of number of triples, query length and query execution time compared to existing approaches. This approach, which is also simple and intuitive, can be easily adopted for representing and querying statements about statements in other knowledge bases. PMID:25750938
An appreciation of Bruce and Young's (1986) serial stage model of face naming after 25 years.
Hanley, J Richard
2011-11-01
The current status of Bruce and Young's (1986) serial model of face naming is discussed 25 years after its original publication. In the first part of the paper, evidence for and against the serial model is reviewed. It is argued that there is no compelling reason why we should abandon Bruce and Young's claim that recall of a name is contingent upon prior retrieval of semantic information about the person. The current status of the claim that people's names are more difficult to recall than the names of objects is then evaluated. Finally, an account of the anatomical location in the brain of Bruce and Young's three processing stages (face familiarity, retrieval of semantic information, retrieval of names) is suggested. In particular, there is evidence that biographical knowledge about familiar people is stored in the right anterior temporal lobes (ATL) and that the left temporal pole (TP) is heavily involved in retrieval of the names of familiar people. The issue of whether these brain areas play a similar role in object processing is also discussed. ©2011 The British Psychological Society.
Early Visual Word Processing Is Flexible: Evidence from Spatiotemporal Brain Dynamics.
Chen, Yuanyuan; Davis, Matthew H; Pulvermüller, Friedemann; Hauk, Olaf
2015-09-01
Visual word recognition is often described as automatic, but the functional locus of top-down effects is still a matter of debate. Do task demands modulate how information is retrieved, or only how it is used? We used EEG/MEG recordings to assess whether, when, and how task contexts modify early retrieval of specific psycholinguistic information in occipitotemporal cortex, an area likely to contribute to early stages of visual word processing. Using a parametric approach, we analyzed the spatiotemporal response patterns of occipitotemporal cortex for orthographic, lexical, and semantic variables in three psycholinguistic tasks: silent reading, lexical decision, and semantic decision. Task modulation of word frequency and imageability effects occurred simultaneously in ventral occipitotemporal regions-in the vicinity of the putative visual word form area-around 160 msec, following task effects on orthographic typicality around 100 msec. Frequency and typicality also produced task-independent effects in anterior temporal lobe regions after 200 msec. The early task modulation for several specific psycholinguistic variables indicates that occipitotemporal areas integrate perceptual input with prior knowledge in a task-dependent manner. Still, later task-independent effects in anterior temporal lobes suggest that word recognition eventually leads to retrieval of semantic information irrespective of task demands. We conclude that even a highly overlearned visual task like word recognition should be described as flexible rather than automatic.
Relative Category-Specific Preservation in Semantic Dementia? Evidence from 35 Cases
ERIC Educational Resources Information Center
Merck, Catherine; Jonin, Pierre-Yves; Vichard, Helene; Boursiquot, Sandrine Le Moal; Leblay, Virginie; Belliard, Serge
2013-01-01
Category-specific deficits have rarely been reported in semantic dementia (SD). To our knowledge, only four previous studies have documented category-specific deficits, and these have focused on the living versus non-living things contrast rather than on more fine-grained semantic categories. This study aimed to determine whether a…
Hypermedia-Assisted Instruction and Second Language Learning: A Semantic-Network-Based Approach.
ERIC Educational Resources Information Center
Liu, Min
This literature review examines a hypermedia learning environment from a semantic network basis and the application of such an environment to second language learning. (A semantic network is defined as a conceptual representation of knowledge in human memory). The discussion is organized under the following headings and subheadings: (1) Advantages…
Premorbid Expertise Produces Category-Specific Impairment in a Domain-General Semantic Disorder
ERIC Educational Resources Information Center
Jefferies, Elizabeth; Rogers, Timothy T.; Ralph, Matthew A. Lambon
2011-01-01
For decades, category-specific semantic impairment--i.e., better comprehension of items from one semantic category than another--has been the driving force behind many claims about the organisation of conceptual knowledge in the brain. Double dissociations between patients with category-specific disorders are widely interpreted as showing that…
Contextual Effect in People with Williams Syndrome
ERIC Educational Resources Information Center
Hsu, Ching-Fen; Tzeng, Ovid J.-L.
2011-01-01
This study was aimed at investigating the semantic integration ability of people with WS in building up a coherent and gist theme from the context of presented sentences. Previous studies have indicated rich lexical semantic knowledge and typical semantic priming in this clinical group, but atypical brainwave patterns have been reported in studies…
A Familiar Pattern? Semantic Memory Contributes to the Enhancement of Visuo-Spatial Memories
ERIC Educational Resources Information Center
Riby, Leigh M.; Orme, Elizabeth
2013-01-01
In this study we quantify for the first time electrophysiological components associated with incorporating long-term semantic knowledge with visuo-spatial information using two variants of a traditional matrix patterns task. Results indicated that the matrix task with greater semantic content was associated with enhanced accuracy and RTs in a…
Short-term Action Intentions Overrule Long-Term Semantic Knowledge
ERIC Educational Resources Information Center
van Elk, M.; van Schie, H.T.; Bekkering, H.
2009-01-01
In the present study, we investigated whether the preparation of an unusual action with an object (e.g. bringing a cup towards the eye) could selectively overrule long-term semantic representations. In the first experiment it was found that unusual action intentions activated short-term semantic goal representations, rather than long-term…
Comprehensive Analysis of Semantic Web Reasoners and Tools: A Survey
ERIC Educational Resources Information Center
Khamparia, Aditya; Pandey, Babita
2017-01-01
Ontologies are emerging as best representation techniques for knowledge based context domains. The continuing need for interoperation, collaboration and effective information retrieval has lead to the creation of semantic web with the help of tools and reasoners which manages personalized information. The future of semantic web lies in an ontology…
Rogers, Timothy T.; Patterson, Karalyn; Jefferies, Elizabeth; Lambon Ralph, Matthew A.
2015-01-01
We present a case-series comparison of patients with cross-modal semantic impairments consequent on either (a) bilateral anterior temporal lobe atrophy in semantic dementia (SD) or (b) left-hemisphere fronto-parietal and/or posterior temporal stroke in semantic aphasia (SA). Both groups were assessed on a new test battery designed to measure how performance is influenced by concept familiarity, typicality and specificity. In line with previous findings, performance in SD was strongly modulated by all of these factors, with better performance for more familiar items (regardless of typicality), for more typical items (regardless of familiarity) and for tasks that did not require very specific classification, consistent with the gradual degradation of conceptual knowledge in SD. The SA group showed significant impairments on all tasks but their sensitivity to familiarity, typicality and specificity was more variable and governed by task-specific effects of these factors on controlled semantic processing. The results are discussed with reference to theories about the complementary roles of representation and manipulation of semantic knowledge. PMID:25934635
Enhancing biomedical text summarization using semantic relation extraction.
Shang, Yue; Li, Yanpeng; Lin, Hongfei; Yang, Zhihao
2011-01-01
Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from multiple documents based on semantic relation extraction. Our approach includes three stages: 1) We extract semantic relations in each sentence using the semantic knowledge representation tool SemRep. 2) We develop a relation-level retrieval method to select the relations most relevant to each query concept and visualize them in a graphic representation. 3) For relations in the relevant set, we extract informative sentences that can interpret them from the document collection to generate text summary using an information retrieval based method. Our major focus in this work is to investigate the contribution of semantic relation extraction to the task of biomedical text summarization. The experimental results on summarization for a set of diseases show that the introduction of semantic knowledge improves the performance and our results are better than the MEAD system, a well-known tool for text summarization.
Mechanisms underlying selecting objects for action
Wulff, Melanie; Laverick, Rosanna; Humphreys, Glyn W.; Wing, Alan M.; Rotshtein, Pia
2015-01-01
We assessed the factors which affect the selection of objects for action, focusing on the role of action knowledge and its modulation by distracters. Fourteen neuropsychological patients and 10 healthy aged-matched controls selected pairs of objects commonly used together among distracters in two contexts: with real objects and with pictures of the same objects presented sequentially on a computer screen. Across both tasks, semantically related distracters led to slower responses and more errors than unrelated distracters and the object actively used for action was selected prior to the object that would be passively held during the action. We identified a sub-group of patients (N = 6) whose accuracy was 2SDs below the controls performances in the real object task. Interestingly, these impaired patients were more affected by the presence of unrelated distracters during both tasks than intact patients and healthy controls. Note that the impaired patients had lesions to left parietal, right anterior temporal and bilateral pre-motor regions. We conclude that: (1) motor procedures guide object selection for action, (2) semantic knowledge affects action-based selection, (3) impaired action decision making is associated with the inability to ignore distracting information and (4) lesions to either the dorsal or ventral visual stream can lead to deficits in making action decisions. Overall, the data indicate that impairments in everyday tasks can be evaluated using a simulated computer task. The implications for rehabilitation are discussed. PMID:25954177
Uncovering Knowledge of Core Syntactic and Semantic Principles in Individuals With Williams Syndrome
Musolino, Julien; Chunyo, Gitana; Landau, Barbara
2011-01-01
We investigate knowledge of core syntactic and semantic principles in individuals with Williams Syndrome (WS). Our study focuses on the logico-syntactic properties of negation and disjunction (or) and tests knowledge of (a) core syntactic relations (scope and c-command), (b) core semantic relations (entailment relations and DeMorgan’s laws of propositional logic), and (c) the relationship between (a) and (b). We examine the performance of individuals with WS, children matched for mental age (MA), and typical adult native speakers of English. Performance on all conditions suggests that knowledge of (a-c) is present and engaged in all three groups. Results also indicate slightly depressed performance on (c) for the WS group, compared to MA, consistent with limitation in processing resources. Implications of these results for competing accounts of language development in WS, as well as for the relevance of WS to the study of cognitive architecture and development are discussed. PMID:21866219
Information integration from heterogeneous data sources: a Semantic Web approach.
Kunapareddy, Narendra; Mirhaji, Parsa; Richards, David; Casscells, S Ward
2006-01-01
Although the decentralized and autonomous implementation of health information systems has made it possible to extend the reach of surveillance systems to a variety of contextually disparate domains, public health use of data from these systems is not primarily anticipated. The Semantic Web has been proposed to address both representational and semantic heterogeneity in distributed and collaborative environments. We introduce a semantic approach for the integration of health data using the Resource Definition Framework (RDF) and the Simple Knowledge Organization System (SKOS) developed by the Semantic Web community.
Semantic amnesia without dementia: documentation of a case.
Rusconi, M L; Zago, S; Basso, A
1997-06-01
We described the case of a patient affected by a progressive semantic memory disorder associated with prevalent temporal lobe atrophy. This deficit seems to be "pure" in the sense that it has not been found to overlap with other cognitive deficits (intellectual, linguistic, perceptual, visuo-spatial etc.) for a long time. Furthermore, despite his impaired semantic knowledge, the autobiographical memory of the patient was largely intact. This case therefore represents a form of "semantic amnesia" without dementia, and supports the hypothesis that there is a partial distinction between "semantic" and "episodic" memory.
Fuzzy Versions of Epistemic and Deontic Logic
NASA Technical Reports Server (NTRS)
Gounder, Ramasamy S.; Esterline, Albert C.
1998-01-01
Epistemic and deontic logics are modal logics, respectively, of knowledge and of the normative concepts of obligation, permission, and prohibition. Epistemic logic is useful in formalizing systems of communicating processes and knowledge and belief in AI (Artificial Intelligence). Deontic logic is useful in computer science wherever we must distinguish between actual and ideal behavior, as in fault tolerance and database integrity constraints. We here discuss fuzzy versions of these logics. In the crisp versions, various axioms correspond to various properties of the structures used in defining the semantics of the logics. Thus, any axiomatic theory will be characterized not only by its axioms but also by the set of properties holding of the corresponding semantic structures. Fuzzy logic does not proceed with axiomatic systems, but fuzzy versions of the semantic properties exist and can be shown to correspond to some of the axioms for the crisp systems in special ways that support dependency networks among assertions in a modal domain. This in turn allows one to implement truth maintenance systems. For the technical development of epistemic logic, and for that of deontic logic. To our knowledge, we are the first to address fuzzy epistemic and fuzzy deontic logic explicitly and to consider the different systems and semantic properties available. We give the syntax and semantics of epistemic logic and discuss the correspondence between axioms of epistemic logic and properties of semantic structures. The same topics are covered for deontic logic. Fuzzy epistemic and fuzzy deontic logic discusses the relationship between axioms and semantic properties for these logics. Our results can be exploited in truth maintenance systems.
Frontotemporal neural systems supporting semantic processing in Alzheimer's disease.
Peelle, Jonathan E; Powers, John; Cook, Philip A; Smith, Edward E; Grossman, Murray
2014-03-01
We hypothesized that semantic memory for object concepts involves both representations of visual feature knowledge in modality-specific association cortex and heteromodal regions that are important for integrating and organizing this semantic knowledge so that it can be used in a flexible, contextually appropriate manner. We examined this hypothesis in an fMRI study of mild Alzheimer's disease (AD). Participants were presented with pairs of printed words and asked whether the words matched on a given visual-perceptual feature (e.g., guitar, violin: SHAPE). The stimuli probed natural kinds and manufactured objects, and the judgments involved shape or color. We found activation of bilateral ventral temporal cortex and left dorsolateral prefrontal cortex during semantic judgments, with AD patients showing less activation of these regions than healthy seniors. Moreover, AD patients showed less ventral temporal activation than did healthy seniors for manufactured objects, but not for natural kinds. We also used diffusion-weighted MRI of white matter to examine fractional anisotropy (FA). Patients with AD showed significantly reduced FA in the superior longitudinal fasciculus and inferior frontal-occipital fasciculus, which carry projections linking temporal and frontal regions of this semantic network. Our results are consistent with the hypothesis that semantic memory is supported in part by a large-scale neural network involving modality-specific association cortex, heteromodal association cortex, and projections between these regions. The semantic deficit in AD thus arises from gray matter disease that affects the representation of feature knowledge and processing its content, as well as white matter disease that interrupts the integrated functioning of this large-scale network.
ERIC Educational Resources Information Center
Adlof, Suzanne M.; Patten, Hannah
2017-01-01
Purpose: This study examined the unique and shared variance that nonword repetition and vocabulary knowledge contribute to children's ability to learn new words. Multiple measures of word learning were used to assess recall and recognition of phonological and semantic information. Method: Fifty children, with a mean age of 8 years (range 5-12…
ERIC Educational Resources Information Center
Bierschenk, Bernhard
Two kinds of perspectives governing the provision and preservation of knowledge, a universal and an ecological perspective, are discussed in this paper. In the first case, scientific observations are represented through a semantic interpretation of facts. This is illustrated with a series of experiments on semantic feature perception in the recall…
Image processing and applications based on visualizing navigation service
NASA Astrophysics Data System (ADS)
Hwang, Chyi-Wen
2015-07-01
When facing the "overabundant" of semantic web information, in this paper, the researcher proposes the hierarchical classification and visualizing RIA (Rich Internet Application) navigation system: Concept Map (CM) + Semantic Structure (SS) + the Knowledge on Demand (KOD) service. The aim of the Multimedia processing and empirical applications testing, was to investigating the utility and usability of this visualizing navigation strategy in web communication design, into whether it enables the user to retrieve and construct their personal knowledge or not. Furthermore, based on the segment markets theory in the Marketing model, to propose a User Interface (UI) classification strategy and formulate a set of hypermedia design principles for further UI strategy and e-learning resources in semantic web communication. These research findings: (1) Irrespective of whether the simple declarative knowledge or the complex declarative knowledge model is used, the "CM + SS + KOD navigation system" has a better cognition effect than the "Non CM + SS + KOD navigation system". However, for the" No web design experience user", the navigation system does not have an obvious cognition effect. (2) The essential of classification in semantic web communication design: Different groups of user have a diversity of preference needs and different cognitive styles in the CM + SS + KOD navigation system.
Progress in The Semantic Analysis of Scientific Code
NASA Technical Reports Server (NTRS)
Stewart, Mark
2000-01-01
This paper concerns a procedure that analyzes aspects of the meaning or semantics of scientific and engineering code. This procedure involves taking a user's existing code, adding semantic declarations for some primitive variables, and parsing this annotated code using multiple, independent expert parsers. These semantic parsers encode domain knowledge and recognize formulae in different disciplines including physics, numerical methods, mathematics, and geometry. The parsers will automatically recognize and document some static, semantic concepts and help locate some program semantic errors. These techniques may apply to a wider range of scientific codes. If so, the techniques could reduce the time, risk, and effort required to develop and modify scientific codes.
Semantic web for integrated network analysis in biomedicine.
Chen, Huajun; Ding, Li; Wu, Zhaohui; Yu, Tong; Dhanapalan, Lavanya; Chen, Jake Y
2009-03-01
The Semantic Web technology enables integration of heterogeneous data on the World Wide Web by making the semantics of data explicit through formal ontologies. In this article, we survey the feasibility and state of the art of utilizing the Semantic Web technology to represent, integrate and analyze the knowledge in various biomedical networks. We introduce a new conceptual framework, semantic graph mining, to enable researchers to integrate graph mining with ontology reasoning in network data analysis. Through four case studies, we demonstrate how semantic graph mining can be applied to the analysis of disease-causal genes, Gene Ontology category cross-talks, drug efficacy analysis and herb-drug interactions analysis.
Lesourd, Mathieu; Budriesi, Carla; Osiurak, François; Nichelli, Paolo F; Bartolo, Angela
2017-12-20
In the literature on apraxia of tool use, it is now accepted that using familiar tools requires semantic and mechanical knowledge. However, mechanical knowledge is nearly always assessed with production tasks, so one may assume that mechanical knowledge and familiar tool use are associated only because of their common motor mechanisms. This notion may be challenged by demonstrating that familiar tool use depends on an alternative tool selection task assessing mechanical knowledge, where alternative uses of tools are assumed according to their physical properties but where actual use of tools is not needed. We tested 21 left brain-damaged patients and 21 matched controls with familiar tool use tasks (pantomime and single tool use), semantic tasks and an alternative tool selection task. The alternative tool selection task accounted for a large amount of variance in the single tool use task and was the best predictor among all the semantic tasks. Concerning the pantomime of tool use task, group and individual results suggested that the integrity of the semantic system and preserved mechanical knowledge are neither necessary nor sufficient to produce pantomimes. These results corroborate the idea that mechanical knowledge is essential when we use tools, even when tasks assessing mechanical knowledge do not require the production of any motor action. Our results also confirm the value of pantomime of tool use, which can be considered as a complex activity involving several cognitive abilities (e.g., communicative skills) rather than the activation of gesture engrams. © 2017 The British Psychological Society.
Koppehele-Gossel, Judith; Schnuerch, Robert; Gibbons, Henning
2018-06-06
This study replicates and extends the findings of Koppehele-Gossel, Schnuerch, and Gibbons (2016) of a posterior semantic asymmetry (PSA) in event-related brain potentials (ERPs), which closely tracks the time course and degree of semantic activation from single visual words. This negativity peaked 300 ms after word onset, was derived by subtracting right- from left-side activity, and was larger in a semantic task compared to two non-semantic control tasks. The validity of the PSA in reflecting the effort to activate word meaning was again attested by a negative correlation between the meaning-specific PSA increase and verbal intelligence, even after controlling for nonverbal intelligence. Extending prior work, current source density (CSD) transformation was used. CSD results were consistent with a left temporo-parietal cortical origin of the PSA. Moreover, no PSA was found for pictorial material, suggesting that the component reflects early semantic processing specific to verbal stimuli. Copyright © 2018 Elsevier Inc. All rights reserved.
Dhaval, Rakesh; Borlawsky, Tara; Ostrander, Michael; Santangelo, Jennifer; Kamal, Jyoti; Payne, Philip R O
2008-11-06
In order to enhance interoperability between enterprise systems, and improve data validity and reliability throughout The Ohio State University Medical Center (OSUMC), we have initiated the development of an ontology-anchored metadata architecture and knowledge collection for our enterprise data warehouse. The metadata and corresponding semantic relationships stored in the OSUMC knowledge collection are intended to promote consistency and interoperability across the heterogeneous clinical, research, business and education information managed within the data warehouse.
Semantic representation of CDC-PHIN vocabulary using Simple Knowledge Organization System.
Zhu, Min; Mirhaji, Parsa
2008-11-06
PHIN Vocabulary Access and Distribution System (VADS) promotes the use of standards based vocabulary within CDC information systems. However, the current PHIN vocabulary representation hinders its wide adoption. Simple Knowledge Organization System (SKOS) is a W3C draft specification to support the formal representation of Knowledge Organization Systems (KOS) within the framework of the Semantic Web. We present a method of adopting SKOS to represent PHIN vocabulary in order to enable automated information sharing and integration.
NASA Astrophysics Data System (ADS)
Wei, Gongjin; Bai, Weijing; Yin, Meifang; Zhang, Songmao
We present a practice of applying the Semantic Web technologies in the domain of Chinese traditional architecture. A knowledge base consisting of one ontology and four rule bases is built to support the automatic generation of animations that demonstrate the construction of various Chinese timber structures based on the user's input. Different Semantic Web formalisms are used, e.g., OWL DL, SWRL and Jess, to capture the domain knowledge, including the wooden components needed for a given building, construction sequence, and the 3D size and position of every piece of wood. Our experience in exploiting the current Semantic Web technologies in real-world application systems indicates their prominent advantages (such as the reasoning facilities and modeling tools) as well as the limitations (such as low efficiency).
van Elk, Michiel; van Schie, Hein; Bekkering, Harold
2014-06-01
Our capacity to use tools and objects is often considered one of the hallmarks of the human species. Many objects greatly extend our bodily capabilities to act in the physical world, such as when using a hammer or a saw. In addition, humans have the remarkable capability to use objects in a flexible fashion and to combine multiple objects in complex actions. We prepare coffee, cook dinner and drive our car. In this review we propose that humans have developed declarative and procedural knowledge, i.e. action semantics that enables us to use objects in a meaningful way. A state-of-the-art review of research on object use is provided, involving behavioral, developmental, neuropsychological and neuroimaging studies. We show that research in each of these domains is characterized by similar discussions regarding (1) the role of object affordances, (2) the relation between goals and means in object use and (3) the functional and neural organization of action semantics. We propose a novel conceptual framework of action semantics to address these issues and to integrate the previous findings. We argue that action semantics entails both multimodal object representations and modality-specific sub-systems, involving manipulation knowledge, functional knowledge and representations of the sensory and proprioceptive consequences of object use. Furthermore, we argue that action semantics are hierarchically organized and selectively activated and used depending on the action intention of the actor and the current task context. Our framework presents an integrative account of multiple findings and perspectives on object use that may guide future studies in this interdisciplinary domain. Copyright © 2013 Elsevier B.V. All rights reserved.
Chiou, Rocco; Lambon Ralph, Matthew A
2018-04-01
Working memory (WM) is a buffer that temporarily maintains information, be it visual or auditory, in an active state, caching its contents for online rehearsal or manipulation. How the brain enables long-term semantic knowledge to affect the WM buffer is a theoretically significant issue awaiting further investigation. In the present study, we capitalise on the knowledge about famous individuals as a 'test-case' to study how it impinges upon WM capacity for human faces and its neural substrate. Using continuous theta-burst transcranial stimulation combined with a psychophysical task probing WM storage for varying contents, we provide compelling evidence that (1) faces (regardless of familiarity) continued to accrue in the WM buffer with longer encoding time, whereas for meaningless stimuli (colour shades) there was little increment; (2) the rate of WM accrual was significantly more efficient for famous faces, compared to unknown faces; (3) the right anterior-ventrolateral temporal lobe (ATL) causally mediated this superior WM storage for famous faces. Specifically, disrupting the ATL (a region tuned to semantic knowledge including person identity) selectively hinders WM accrual for celebrity faces while leaving the accrual for unfamiliar faces intact. Further, this 'semantically-accelerated' storage is impervious to disruption of the right middle frontal gyrus and vertex, supporting the specific and causative contribution of the right ATL. Our finding advances the understanding of the neural architecture of WM, demonstrating that it depends on interaction with long-term semantic knowledge underpinned by the ATL, which causally expands the WM buffer when visual content carries semantic information. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
Lexical leverage: Category knowledge boosts real-time novel word recognition in two-year- olds
Borovsky, Arielle; Ellis, Erica M.; Evans, Julia L.; Elman, Jeffrey L.
2016-01-01
Recent research suggests that infants tend to add words to their vocabulary that are semantically related to other known words, though it is not clear why this pattern emerges. In this paper, we explore whether infants to leverage their existing vocabulary and semantic knowledge when interpreting novel label-object mappings in real-time. We initially identified categorical domains for which individual 24-month-old infants have relatively higher and lower levels of knowledge, irrespective of overall vocabulary size. Next, we taught infants novel words in these higher and lower knowledge domains and then asked if their subsequent real-time recognition of these items varied as a function of their category knowledge. While our participants successfully acquired the novel label -object mappings in our task, there were important differences in the way infants recognized these words in real time. Namely, infants showed more robust recognition of high (vs. low) domain knowledge words. These findings suggest that dense semantic structure facilitates early word learning and real-time novel word recognition. PMID:26452444
Dönitz, Jürgen; Wingender, Edgar
2012-01-01
The semantic web depends on the use of ontologies to let electronic systems interpret contextual information. Optimally, the handling and access of ontologies should be completely transparent to the user. As a means to this end, we have developed a service that attempts to bridge the gap between experts in a certain knowledge domain, ontologists, and application developers. The ontology-based answers (OBA) service introduced here can be embedded into custom applications to grant access to the classes of ontologies and their relations as most important structural features as well as to information encoded in the relations between ontology classes. Thus computational biologists can benefit from ontologies without detailed knowledge about the respective ontology. The content of ontologies is mapped to a graph of connected objects which is compatible to the object-oriented programming style in Java. Semantic functions implement knowledge about the complex semantics of an ontology beyond the class hierarchy and "partOf" relations. By using these OBA functions an application can, for example, provide a semantic search function, or (in the examples outlined) map an anatomical structure to the organs it belongs to. The semantic functions relieve the application developer from the necessity of acquiring in-depth knowledge about the semantics and curation guidelines of the used ontologies by implementing the required knowledge. The architecture of the OBA service encapsulates the logic to process ontologies in order to achieve a separation from the application logic. A public server with the current plugins is available and can be used with the provided connector in a custom application in scenarios analogous to the presented use cases. The server and the client are freely available if a project requires the use of custom plugins or non-public ontologies. The OBA service and further documentation is available at http://www.bioinf.med.uni-goettingen.de/projects/oba.
Dönitz, Jürgen; Wingender, Edgar
2012-01-01
The semantic web depends on the use of ontologies to let electronic systems interpret contextual information. Optimally, the handling and access of ontologies should be completely transparent to the user. As a means to this end, we have developed a service that attempts to bridge the gap between experts in a certain knowledge domain, ontologists, and application developers. The ontology-based answers (OBA) service introduced here can be embedded into custom applications to grant access to the classes of ontologies and their relations as most important structural features as well as to information encoded in the relations between ontology classes. Thus computational biologists can benefit from ontologies without detailed knowledge about the respective ontology. The content of ontologies is mapped to a graph of connected objects which is compatible to the object-oriented programming style in Java. Semantic functions implement knowledge about the complex semantics of an ontology beyond the class hierarchy and “partOf” relations. By using these OBA functions an application can, for example, provide a semantic search function, or (in the examples outlined) map an anatomical structure to the organs it belongs to. The semantic functions relieve the application developer from the necessity of acquiring in-depth knowledge about the semantics and curation guidelines of the used ontologies by implementing the required knowledge. The architecture of the OBA service encapsulates the logic to process ontologies in order to achieve a separation from the application logic. A public server with the current plugins is available and can be used with the provided connector in a custom application in scenarios analogous to the presented use cases. The server and the client are freely available if a project requires the use of custom plugins or non-public ontologies. The OBA service and further documentation is available at http://www.bioinf.med.uni-goettingen.de/projects/oba PMID:23060901
Jiang, Guoqian; Solbrig, Harold R; Chute, Christopher G
2011-01-01
A source of semantically coded Adverse Drug Event (ADE) data can be useful for identifying common phenotypes related to ADEs. We proposed a comprehensive framework for building a standardized ADE knowledge base (called ADEpedia) through combining ontology-based approach with semantic web technology. The framework comprises four primary modules: 1) an XML2RDF transformation module; 2) a data normalization module based on NCBO Open Biomedical Annotator; 3) a RDF store based persistence module; and 4) a front-end module based on a Semantic Wiki for the review and curation. A prototype is successfully implemented to demonstrate the capability of the system to integrate multiple drug data and ontology resources and open web services for the ADE data standardization. A preliminary evaluation is performed to demonstrate the usefulness of the system, including the performance of the NCBO annotator. In conclusion, the semantic web technology provides a highly scalable framework for ADE data source integration and standard query service.
ERIC Educational Resources Information Center
Gainotti, Guido
2011-01-01
In recent years, the anatomical and functional bases of conceptual activity have attracted a growing interest. In particular, Patterson and Lambon-Ralph have proposed the existence, in the anterior parts of the temporal lobes, of a mechanism (the "amodal semantic hub") supporting the interactive activation of semantic representations in all…
ERIC Educational Resources Information Center
Maguire, Mandy J.; Brier, Matthew R.; Ferree, Thomas C.
2010-01-01
Despite the importance of semantic relationships to our understanding of semantic knowledge, the nature of the neural processes underlying these abilities are not well understood. In order to investigate these processes, 20 healthy adults listened to thematically related (e.g., leash-dog), taxonomically related (e.g., horse-dog), or unrelated…
ERIC Educational Resources Information Center
Kuchinke, Lars; van der Meer, Elke; Krueger, Frank
2009-01-01
Conceptual knowledge of our world is represented in semantic memory in terms of concepts and semantic relations between concepts. We used functional magnetic resonance imaging (fMRI) to examine the cortical regions underlying the processing of sequential and taxonomic relations. Participants were presented verbal cues and performed three tasks:…
Knowledge-Base Semantic Gap Analysis for the Vulnerability Detection
NASA Astrophysics Data System (ADS)
Wu, Raymond; Seki, Keisuke; Sakamoto, Ryusuke; Hisada, Masayuki
Web security became an alert in internet computing. To cope with ever-rising security complexity, semantic analysis is proposed to fill-in the gap that the current approaches fail to commit. Conventional methods limit their focus to the physical source codes instead of the abstraction of semantics. It bypasses new types of vulnerability and causes tremendous business loss.
Semantic Relevance, Domain Specificity and the Sensory/Functional Theory of Category-Specificity
ERIC Educational Resources Information Center
Sartori, Giuseppe; Gnoato, Francesca; Mariani, Ilenia; Prioni, Sara; Lombardi, Luigi
2007-01-01
According to the sensory/functional theory of semantic memory, Living items rely more on Sensory knowledge than Non-living ones. The sensory/functional explanation of category-specificity assumes that semantic features are organised on the basis of their content. We report here a study on DAT patients with impaired performance on Living items and…
The Benefits of Sensorimotor Knowledge: Body-Object Interaction Facilitates Semantic Processing
ERIC Educational Resources Information Center
Siakaluk, Paul D.; Pexman, Penny M.; Sears, Christopher R.; Wilson, Kim; Locheed, Keri; Owen, William J.
2008-01-01
This article examined the effects of body-object interaction (BOI) on semantic processing. BOI measures perceptions of the ease with which a human body can physically interact with a word's referent. In Experiment 1, BOI effects were examined in 2 semantic categorization tasks (SCT) in which participants decided if words are easily imageable.…
An fMRI Study of Sentence-Embedded Lexical-Semantic Decision in Children and Adults
ERIC Educational Resources Information Center
Moore-Parks, Erin Nicole; Burns, Erin L.; Bazzill, Rebecca; Levy, Sarah; Posada, Valerie; Muller, Ralph-Axel
2010-01-01
Lexical-semantic knowledge is a core language component that undergoes prolonged development throughout childhood and is therefore highly amenable to developmental studies. Most previous lexical-semantic functional MRI (fMRI) studies have been limited to single-word or word-pair tasks, outside a sentence context. Our objective was to investigate…
Hassanpour, Saeed; O'Connor, Martin J; Das, Amar K
2013-08-12
A variety of informatics approaches have been developed that use information retrieval, NLP and text-mining techniques to identify biomedical concepts and relations within scientific publications or their sentences. These approaches have not typically addressed the challenge of extracting more complex knowledge such as biomedical definitions. In our efforts to facilitate knowledge acquisition of rule-based definitions of autism phenotypes, we have developed a novel semantic-based text-mining approach that can automatically identify such definitions within text. Using an existing knowledge base of 156 autism phenotype definitions and an annotated corpus of 26 source articles containing such definitions, we evaluated and compared the average rank of correctly identified rule definition or corresponding rule template using both our semantic-based approach and a standard term-based approach. We examined three separate scenarios: (1) the snippet of text contained a definition already in the knowledge base; (2) the snippet contained an alternative definition for a concept in the knowledge base; and (3) the snippet contained a definition not in the knowledge base. Our semantic-based approach had a higher average rank than the term-based approach for each of the three scenarios (scenario 1: 3.8 vs. 5.0; scenario 2: 2.8 vs. 4.9; and scenario 3: 4.5 vs. 6.2), with each comparison significant at the p-value of 0.05 using the Wilcoxon signed-rank test. Our work shows that leveraging existing domain knowledge in the information extraction of biomedical definitions significantly improves the correct identification of such knowledge within sentences. Our method can thus help researchers rapidly acquire knowledge about biomedical definitions that are specified and evolving within an ever-growing corpus of scientific publications.
tESA: a distributional measure for calculating semantic relatedness.
Rybinski, Maciej; Aldana-Montes, José Francisco
2016-12-28
Semantic relatedness is a measure that quantifies the strength of a semantic link between two concepts. Often, it can be efficiently approximated with methods that operate on words, which represent these concepts. Approximating semantic relatedness between texts and concepts represented by these texts is an important part of many text and knowledge processing tasks of crucial importance in the ever growing domain of biomedical informatics. The problem of most state-of-the-art methods for calculating semantic relatedness is their dependence on highly specialized, structured knowledge resources, which makes these methods poorly adaptable for many usage scenarios. On the other hand, the domain knowledge in the Life Sciences has become more and more accessible, but mostly in its unstructured form - as texts in large document collections, which makes its use more challenging for automated processing. In this paper we present tESA, an extension to a well known Explicit Semantic Relatedness (ESA) method. In our extension we use two separate sets of vectors, corresponding to different sections of the articles from the underlying corpus of documents, as opposed to the original method, which only uses a single vector space. We present an evaluation of Life Sciences domain-focused applicability of both tESA and domain-adapted Explicit Semantic Analysis. The methods are tested against a set of standard benchmarks established for the evaluation of biomedical semantic relatedness quality. Our experiments show that the propsed method achieves results comparable with or superior to the current state-of-the-art methods. Additionally, a comparative discussion of the results obtained with tESA and ESA is presented, together with a study of the adaptability of the methods to different corpora and their performance with different input parameters. Our findings suggest that combined use of the semantics from different sections (i.e. extending the original ESA methodology with the use of title vectors) of the documents of scientific corpora may be used to enhance the performance of a distributional semantic relatedness measures, which can be observed in the largest reference datasets. We also present the impact of the proposed extension on the size of distributional representations.
New Semantic Learning in Patients With Large Medial Temporal Lobe Lesions
Bayley, P.J.; O'Reilly, R.C.; Curran, T.; Squire, L.R.
2008-01-01
Two patients with large lesions of the medial temporal lobe were given four tests of semantic knowledge that could only have been acquired after the onset of their amnesia. In contrast to previous studies of postmorbid semantic learning, correct answers could be based on a simple, nonspecific sense of familiarity about single words, faces, or objects. According to recent computational models (for example, Norman and O'Reilly (2003) Psychol Rev 110:611–646), this characteristic should be optimal for detecting the kind of semantic learning that might be supported directly by the neocortex. Both patients exhibited some capacity for new learning, albeit at a level substantially below control performances. Notably, the correct answers appeared to reflect declarative memory. It was not the case that the correct answers simply popped out in some automatic way in the absence of any additional knowledge about the items. Rather, the few correct choices made by the patients tended to be accompanied by additional information about the chosen items, and the available knowledge appeared to be similar qualitatively to the kind of factual knowledge that healthy individuals gradually acquire over the years. The results are consistent with the idea that neocortical structures outside the medial temporal lobe are able to support some semantic learning, albeit to a very limited extent. Alternatively, the small amount of learning detected in the present study could depend on tissue within the posterior medial temporal lobe that remains intact in both patients. PMID:18306299
ERIC Educational Resources Information Center
Jasinska, Kaja K.; Petitto, Laura-Ann
2018-01-01
Bilingual children's reading as a function of age of first bilingual language exposure (AoE) was examined. Bilingual (varied AoE) and monolingual children (N = 421) were compared in their English language and reading abilities (6-10 years) using phonological awareness, semantic knowledge, and reading tasks. Structural equation modeling was applied…
Prior Knowledge about Objects Determines Neural Color Representation in Human Visual Cortex.
Vandenbroucke, A R E; Fahrenfort, J J; Meuwese, J D I; Scholte, H S; Lamme, V A F
2016-04-01
To create subjective experience, our brain must translate physical stimulus input by incorporating prior knowledge and expectations. For example, we perceive color and not wavelength information, and this in part depends on our past experience with colored objects ( Hansen et al. 2006; Mitterer and de Ruiter 2008). Here, we investigated the influence of object knowledge on the neural substrates underlying subjective color vision. In a functional magnetic resonance imaging experiment, human subjects viewed a color that lay midway between red and green (ambiguous with respect to its distance from red and green) presented on either typical red (e.g., tomato), typical green (e.g., clover), or semantically meaningless (nonsense) objects. Using decoding techniques, we could predict whether subjects viewed the ambiguous color on typical red or typical green objects based on the neural response of veridical red and green. This shift of neural response for the ambiguous color did not occur for nonsense objects. The modulation of neural responses was observed in visual areas (V3, V4, VO1, lateral occipital complex) involved in color and object processing, as well as frontal areas. This demonstrates that object memory influences wavelength information relatively early in the human visual system to produce subjective color vision. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Heat-Passing Framework for Robust Interpretation of Data in Networks
Fang, Yi; Sun, Mengtian; Ramani, Karthik
2015-01-01
Researchers are regularly interested in interpreting the multipartite structure of data entities according to their functional relationships. Data is often heterogeneous with intricately hidden inner structure. With limited prior knowledge, researchers are likely to confront the problem of transforming this data into knowledge. We develop a new framework, called heat-passing, which exploits intrinsic similarity relationships within noisy and incomplete raw data, and constructs a meaningful map of the data. The proposed framework is able to rank, cluster, and visualize the data all at once. The novelty of this framework is derived from an analogy between the process of data interpretation and that of heat transfer, in which all data points contribute simultaneously and globally to reveal intrinsic similarities between regions of data, meaningful coordinates for embedding the data, and exemplar data points that lie at optimal positions for heat transfer. We demonstrate the effectiveness of the heat-passing framework for robustly partitioning the complex networks, analyzing the globin family of proteins and determining conformational states of macromolecules in the presence of high levels of noise. The results indicate that the methodology is able to reveal functionally consistent relationships in a robust fashion with no reference to prior knowledge. The heat-passing framework is very general and has the potential for applications to a broad range of research fields, for example, biological networks, social networks and semantic analysis of documents. PMID:25668316
Desai, Rutvik H.; Graves, William W.; Conant, Lisa L.
2009-01-01
Semantic memory refers to knowledge about people, objects, actions, relations, self, and culture acquired through experience. The neural systems that store and retrieve this information have been studied for many years, but a consensus regarding their identity has not been reached. Using strict inclusion criteria, we analyzed 120 functional neuroimaging studies focusing on semantic processing. Reliable areas of activation in these studies were identified using the activation likelihood estimate (ALE) technique. These activations formed a distinct, left-lateralized network comprised of 7 regions: posterior inferior parietal lobe, middle temporal gyrus, fusiform and parahippocampal gyri, dorsomedial prefrontal cortex, inferior frontal gyrus, ventromedial prefrontal cortex, and posterior cingulate gyrus. Secondary analyses showed specific subregions of this network associated with knowledge of actions, manipulable artifacts, abstract concepts, and concrete concepts. The cortical regions involved in semantic processing can be grouped into 3 broad categories: posterior multimodal and heteromodal association cortex, heteromodal prefrontal cortex, and medial limbic regions. The expansion of these regions in the human relative to the nonhuman primate brain may explain uniquely human capacities to use language productively, plan, solve problems, and create cultural and technological artifacts, all of which depend on the fluid and efficient retrieval and manipulation of semantic knowledge. PMID:19329570
Semantic Mappings and Locality of Nursing Diagnostic Concepts in UMLS
Kim, Tae Youn; Coenen, Amy; Hardiker, Nicholas
2011-01-01
One solution for enhancing the interoperability between nursing information systems, given the availability of multiple nursing terminologies, is to cross-map existing nursing concepts. The Unified Medical Language System (UMLS) developed and distributed by the National Library of Medicine (NLM) is a knowledge resource containing cross-mappings of various terminologies in a unified framework. While the knowledge resource has been available for the last two decades, little research on the representation of nursing terminologies in UMLS has been conducted. As a first step, UMLS semantic mappings and concept locality were examined for nursing diagnostic concepts or problems selected from three terminologies (i.e., CCC, ICNP, and NANDA-I) along with corresponding SNOMED CT concepts. The evaluation of UMLS semantic mappings was conducted by measuring the proportion of concordance between UMLS and human expert mappings. The semantic locality of nursing diagnostic concepts was assessed by examining the associations of select concepts and the placement of the nursing concepts on the Semantic Network and Group. The study found that the UMLS mappings of CCC and NANDA-I concepts to SNOMED CT were highly concordant to expert mappings. The level of concordance in mappings of ICNP to SNOMED CT, CCC and NANDA-I within UMLS was relatively low, indicating the need for further research and development. Likewise, the semantic locality of ICNP concepts could be further improved. Various stakeholders need to collaborate to enhance the NLM knowledge resource and the interoperability of nursing data within the discipline as well as across health-related disciplines. PMID:21951759
Triangulation of the neurocomputational architecture underpinning reading aloud
Hoffman, Paul; Lambon Ralph, Matthew A.; Woollams, Anna M.
2015-01-01
The goal of cognitive neuroscience is to integrate cognitive models with knowledge about underlying neural machinery. This significant challenge was explored in relation to word reading, where sophisticated computational-cognitive models exist but have made limited contact with neural data. Using distortion-corrected functional MRI and dynamic causal modeling, we investigated the interactions between brain regions dedicated to orthographic, semantic, and phonological processing while participants read words aloud. We found that the lateral anterior temporal lobe exhibited increased activation when participants read words with irregular spellings. This area is implicated in semantic processing but has not previously been considered part of the reading network. We also found meaningful individual differences in the activation of this region: Activity was predicted by an independent measure of the degree to which participants use semantic knowledge to read. These characteristics are predicted by the connectionist Triangle Model of reading and indicate a key role for semantic knowledge in reading aloud. Premotor regions associated with phonological processing displayed the reverse characteristics. Changes in the functional connectivity of the reading network during irregular word reading also were consistent with semantic recruitment. These data support the view that reading aloud is underpinned by the joint operation of two neural pathways. They reveal that (i) the ATL is an important element of the ventral semantic pathway and (ii) the division of labor between the two routes varies according to both the properties of the words being read and individual differences in the degree to which participants rely on each route. PMID:26124121
The Emergence of Knowledge and How it Supports the Memory for Novel Related Information.
Sommer, Tobias
2017-03-01
Current theories suggest that memories for novel information and events, over time and with repeated retrieval, lose the association to their initial learning context. They are consolidated into a more stable form and transformed into semantic knowledge, that is, semanticized. Novel, related information can then be rapidly integrated into such knowledge, leading to superior memory. We tested these hypotheses in a longitudinal, 302-day, human functional magnetic resonance imaging study in which participants first overlearned and consolidated associative structures. This phase was associated with a shift from hippocampal- to ventrolateral prefrontal cortex (vlPFC)-mediated retrieval, consistent with semanticization. Next, participants encoded novel, related information whose encoding into the already acquired knowledge was orchestrated by the ventromedial prefrontal cortex. Novel related information exhibited reduced forgetting compared with novel control information, which corresponded to a faster shift from hippocampal- to vlPFC-mediated retrieval. In sum, the current results suggest that memory for novel information can be enhanced by anchoring it to prior knowledge via acceleration of the processes observed during semanticization. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Using background knowledge for picture organization and retrieval
NASA Astrophysics Data System (ADS)
Quintana, Yuri
1997-01-01
A picture knowledge base management system is described that is used to represent, organize and retrieve pictures from a frame knowledge base. Experiments with human test subjects were conducted to obtain further descriptions of pictures from news magazines. These descriptions were used to represent the semantic content of pictures in frame representations. A conceptual clustering algorithm is described which organizes pictures not only on the observable features, but also on implicit properties derived from the frame representations. The algorithm uses inheritance reasoning to take into account background knowledge in the clustering. The algorithm creates clusters of pictures using a group similarity function that is based on the gestalt theory of picture perception. For each cluster created, a frame is generated which describes the semantic content of pictures in the cluster. Clustering and retrieval experiments were conducted with and without background knowledge. The paper shows how the use of background knowledge and semantic similarity heuristics improves the speed, precision, and recall of queries processed. The paper concludes with a discussion of how natural language processing of can be used to assist in the development of knowledge bases and the processing of user queries.
Neural bases of event knowledge and syntax integration in comprehension of complex sentences.
Malaia, Evie; Newman, Sharlene
2015-01-01
Comprehension of complex sentences is necessarily supported by both syntactic and semantic knowledge, but what linguistic factors trigger a readers' reliance on a specific system? This functional neuroimaging study orthogonally manipulated argument plausibility and verb event type to investigate cortical bases of the semantic effect on argument comprehension during reading. The data suggest that telic verbs facilitate online processing by means of consolidating the event schemas in episodic memory and by easing the computation of syntactico-thematic hierarchies in the left inferior frontal gyrus. The results demonstrate that syntax-semantics integration relies on trade-offs among a distributed network of regions for maximum comprehension efficiency.
Taxonomy, Ontology and Semantics at Johnson Space Center
NASA Technical Reports Server (NTRS)
Berndt, Sarah Ann
2011-01-01
At NASA Johnson Space Center (JSC), the Chief Knowledge Officer has been developing the JSC Taxonomy to capitalize on the accomplishments of yesterday while maintaining the flexibility needed for the evolving information environment of today. A clear vision and scope for the semantic system is integral to its success. The vision for the JSC Taxonomy is to connect information stovepipes to present a unified view for information and knowledge across the Center, across organizations, and across decades. Semantic search at JSC means seemless integration of disparate information sets into a single interface. Ever increasing use, interest, and organizational participation mark successful integration and provide the framework for future application.
NASA Astrophysics Data System (ADS)
Sauermann, Leo; Kiesel, Malte; Schumacher, Kinga; Bernardi, Ansgar
In diesem Beitrag wird gezeigt, wie der Arbeitsplatz der Zukunft aussehen könnte und wo das Semantic Web neue Möglichkeiten eröffnet. Dazu werden Ansätze aus dem Bereich Semantic Web, Knowledge Representation, Desktop-Anwendungen und Visualisierung vorgestellt, die es uns ermöglichen, die bestehenden Daten eines Benutzers neu zu interpretieren und zu verwenden. Dabei bringt die Kombination von Semantic Web und Desktop Computern besondere Vorteile - ein Paradigma, das unter dem Titel Semantic Desktop bekannt ist. Die beschriebenen Möglichkeiten der Applikationsintegration sind aber nicht auf den Desktop beschränkt, sondern können genauso in Web-Anwendungen Verwendung finden.
Automatically exposing OpenLifeData via SADI semantic Web Services.
González, Alejandro Rodríguez; Callahan, Alison; Cruz-Toledo, José; Garcia, Adrian; Egaña Aranguren, Mikel; Dumontier, Michel; Wilkinson, Mark D
2014-01-01
Two distinct trends are emerging with respect to how data is shared, collected, and analyzed within the bioinformatics community. First, Linked Data, exposed as SPARQL endpoints, promises to make data easier to collect and integrate by moving towards the harmonization of data syntax, descriptive vocabularies, and identifiers, as well as providing a standardized mechanism for data access. Second, Web Services, often linked together into workflows, normalize data access and create transparent, reproducible scientific methodologies that can, in principle, be re-used and customized to suit new scientific questions. Constructing queries that traverse semantically-rich Linked Data requires substantial expertise, yet traditional RESTful or SOAP Web Services cannot adequately describe the content of a SPARQL endpoint. We propose that content-driven Semantic Web Services can enable facile discovery of Linked Data, independent of their location. We use a well-curated Linked Dataset - OpenLifeData - and utilize its descriptive metadata to automatically configure a series of more than 22,000 Semantic Web Services that expose all of its content via the SADI set of design principles. The OpenLifeData SADI services are discoverable via queries to the SHARE registry and easy to integrate into new or existing bioinformatics workflows and analytical pipelines. We demonstrate the utility of this system through comparison of Web Service-mediated data access with traditional SPARQL, and note that this approach not only simplifies data retrieval, but simultaneously provides protection against resource-intensive queries. We show, through a variety of different clients and examples of varying complexity, that data from the myriad OpenLifeData can be recovered without any need for prior-knowledge of the content or structure of the SPARQL endpoints. We also demonstrate that, via clients such as SHARE, the complexity of federated SPARQL queries is dramatically reduced.
Ontology-Based Search of Genomic Metadata.
Fernandez, Javier D; Lenzerini, Maurizio; Masseroli, Marco; Venco, Francesco; Ceri, Stefano
2016-01-01
The Encyclopedia of DNA Elements (ENCODE) is a huge and still expanding public repository of more than 4,000 experiments and 25,000 data files, assembled by a large international consortium since 2007; unknown biological knowledge can be extracted from these huge and largely unexplored data, leading to data-driven genomic, transcriptomic, and epigenomic discoveries. Yet, search of relevant datasets for knowledge discovery is limitedly supported: metadata describing ENCODE datasets are quite simple and incomplete, and not described by a coherent underlying ontology. Here, we show how to overcome this limitation, by adopting an ENCODE metadata searching approach which uses high-quality ontological knowledge and state-of-the-art indexing technologies. Specifically, we developed S.O.S. GeM (http://www.bioinformatics.deib.polimi.it/SOSGeM/), a system supporting effective semantic search and retrieval of ENCODE datasets. First, we constructed a Semantic Knowledge Base by starting with concepts extracted from ENCODE metadata, matched to and expanded on biomedical ontologies integrated in the well-established Unified Medical Language System. We prove that this inference method is sound and complete. Then, we leveraged the Semantic Knowledge Base to semantically search ENCODE data from arbitrary biologists' queries. This allows correctly finding more datasets than those extracted by a purely syntactic search, as supported by the other available systems. We empirically show the relevance of found datasets to the biologists' queries.
Papagno, Costanza; Semenza, Carlo; Girelli, Luisa
2013-11-01
This study describes a follow-up investigation of numerical abilities and visuospatial memory in a patient suffering from semantic dementia whose progressive decline of semantic memory variably affected different types of knowledge. Crucially, we investigated in detail her outstanding performance with Sudoku that has been only anecdotally reported in the previous literature. We tested spatial cognition and memory, body representation, number processing, calculation, and Sudoku tasks, and we compared the patient's performance with that of matched controls. In agreement with the neuroanatomical data, showing substantial sparing of the parietal lobes in the face of severe atrophy of the temporal (and frontal) regions, we report full preservation of skills known to be supported by intact parietal-basal ganglia networks, and impaired knowledge related to long-term stored declarative information mediated by temporal regions. Performance in tasks sensitive to parietal dysfunction (such as right-left orientation, finger gnosis, writing, and visuospatial memory) was normal; within the numerical domain, preserved quantity-based number knowledge dissociated from increasing difficulties with nonquantitative number knowledge (such as knowledge of encyclopedic and personal number facts) and arithmetic facts knowledge. This case confirms the relation between numbers and space, and, although indirectly, their anatomical correlates, underlining which abilities are preserved in the case of severe semantic loss. In addition, although Sudoku is not inherently numerical, the patient was able to solve even the most difficult pattern, provided that it required digits and not letters, showing that digits have, in any case, a specific status. PsycINFO Database Record (c) 2013 APA, all rights reserved.
The selective preservation of colour naming in semantic dementia.
Robinson, G; Cipolotti, L
2001-01-01
This paper documents a series of seven patients with semantic dementia who showed a selective preservation in colour naming. This was in the context of a pervasive impairment in naming nouns across a wide range of other semantic categories. To our knowledge, this is the first series of patients with semantic dementia documenting a selective preservation of colour naming. These findings are discussed in the light of current theoretical accounts of category-specific effects and the possible contribution of imageability to this selective preservation of colours.
Semantic Metrics for Analysis of Software
NASA Technical Reports Server (NTRS)
Etzkorn, Letha H.; Cox, Glenn W.; Farrington, Phil; Utley, Dawn R.; Ghalston, Sampson; Stein, Cara
2005-01-01
A recently conceived suite of object-oriented software metrics focus is on semantic aspects of software, in contradistinction to traditional software metrics, which focus on syntactic aspects of software. Semantic metrics represent a more human-oriented view of software than do syntactic metrics. The semantic metrics of a given computer program are calculated by use of the output of a knowledge-based analysis of the program, and are substantially more representative of software quality and more readily comprehensible from a human perspective than are the syntactic metrics.
A fuzzy-ontology-oriented case-based reasoning framework for semantic diabetes diagnosis.
El-Sappagh, Shaker; Elmogy, Mohammed; Riad, A M
2015-11-01
Case-based reasoning (CBR) is a problem-solving paradigm that uses past knowledge to interpret or solve new problems. It is suitable for experience-based and theory-less problems. Building a semantically intelligent CBR that mimic the expert thinking can solve many problems especially medical ones. Knowledge-intensive CBR using formal ontologies is an evolvement of this paradigm. Ontologies can be used for case representation and storage, and it can be used as a background knowledge. Using standard medical ontologies, such as SNOMED CT, enhances the interoperability and integration with the health care systems. Moreover, utilizing vague or imprecise knowledge further improves the CBR semantic effectiveness. This paper proposes a fuzzy ontology-based CBR framework. It proposes a fuzzy case-base OWL2 ontology, and a fuzzy semantic retrieval algorithm that handles many feature types. This framework is implemented and tested on the diabetes diagnosis problem. The fuzzy ontology is populated with 60 real diabetic cases. The effectiveness of the proposed approach is illustrated with a set of experiments and case studies. The resulting system can answer complex medical queries related to semantic understanding of medical concepts and handling of vague terms. The resulting fuzzy case-base ontology has 63 concepts, 54 (fuzzy) object properties, 138 (fuzzy) datatype properties, 105 fuzzy datatypes, and 2640 instances. The system achieves an accuracy of 97.67%. We compare our framework with existing CBR systems and a set of five machine-learning classifiers; our system outperforms all of these systems. Building an integrated CBR system can improve its performance. Representing CBR knowledge using the fuzzy ontology and building a case retrieval algorithm that treats different features differently improves the accuracy of the resulting systems. Copyright © 2015 Elsevier B.V. All rights reserved.
[Artificial intelligence meeting neuropsychology. Semantic memory in normal and pathological aging].
Aimé, Xavier; Charlet, Jean; Maillet, Didier; Belin, Catherine
2015-03-01
Artificial intelligence (IA) is the subject of much research, but also many fantasies. It aims to reproduce human intelligence in its learning capacity, knowledge storage and computation. In 2014, the Defense Advanced Research Projects Agency (DARPA) started the restoring active memory (RAM) program that attempt to develop implantable technology to bridge gaps in the injured brain and restore normal memory function to people with memory loss caused by injury or disease. In another IA's field, computational ontologies (a formal and shared conceptualization) try to model knowledge in order to represent a structured and unambiguous meaning of the concepts of a target domain. The aim of these structures is to ensure a consensual understanding of their meaning and a univariant use (the same concept is used by all to categorize the same individuals). The first representations of knowledge in the AI's domain are largely based on model tests of semantic memory. This one, as a component of long-term memory is the memory of words, ideas, concepts. It is the only declarative memory system that resists so remarkably to the effects of age. In contrast, non-specific cognitive changes may decrease the performance of elderly in various events and instead report difficulties of access to semantic representations that affect the semantics stock itself. Some dementias, like semantic dementia and Alzheimer's disease, are linked to alteration of semantic memory. We propose in this paper, using the computational ontologies model, a formal and relatively thin modeling, in the service of neuropsychology: 1) for the practitioner with decision support systems, 2) for the patient as cognitive prosthesis outsourced, and 3) for the researcher to study semantic memory.
How Semantic Radicals in Chinese characters Facilitate Hierarchical Category-Based Induction.
Wang, Xiaoxi; Ma, Xie; Tao, Yun; Tao, Yachen; Li, Hong
2018-04-03
Prior studies indicate that the semantic radical in Chinese characters contains category information that can support the independent retrieval of category information through the lexical network to the conceptual network. Inductive reasoning relies on category information; thus, semantic radicals may influence inductive reasoning. As most natural concepts are hierarchically structured in the human brain, this study examined how semantic radicals impact inductive reasoning for hierarchical concepts. The study used animal and plant nouns, organized in basic, superordinate, and subordinate levels; half had a semantic radical and half did not. Eighteen participants completed an inductive reasoning task. Behavioural and event-related potential (ERP) data were collected. The behavioural results showed that participants reacted faster and more accurately in the with-semantic-radical condition than in the without-semantic-radical condition. For the ERPs, differences between the conditions were found, and these differences lasted from the very early cognitive processing stage (i.e., the N1 time window) to the relatively late processing stages (i.e., the N400 and LPC time windows). Semantic radicals can help to distinguish the hierarchies earlier (in the N400 period) than characters without a semantic radical (in the LPC period). These results provide electrophysiological evidence that semantic radicals may improve sensitivity to distinguish between hierarchical concepts.
ERIC Educational Resources Information Center
Hall, Jessica; McGregor, Karla K.; Oleson, Jacob
2017-01-01
Purpose: The purpose of this study is to determine whether deficits in executive function and lexical-semantic memory compromise the linguistic performance of young adults with specific learning disabilities (LD) enrolled in postsecondary studies. Method: One hundred eighty-five students with LD (n = 53) or normal language development (ND, n =…
Gainotti, Guido
2015-04-01
The present review aimed to check two proposals alternative to the original version of the 'semantic hub' hypothesis, based on semantic dementia (SD) data, which assumed that left and right anterior temporal lobes (ATLs) store in a unitary, amodal format all kinds of semantic representations. The first alternative proposal is that the right ATL might subsume non-verbal representations and the left ATL lexical-semantic representations and that only in the advanced stages of SD, when atrophy affects the ATLs bilaterally, the semantic impairment becomes 'multi-modal'. The second alternative suggestion is that right and left ATLs might underlie two different domains of knowledge, because general conceptual knowledge might be supported by the left ATL, and social cognition by the right ATL. Results of the review substantially support the first proposal, showing that the right ATL subsumes non-verbal representations and the left ATL lexical-semantic representations. They are less conclusive about the second suggestion, because the right ATL seems to play a more important role in behavioral and emotional functions than in higher level social cognition. Copyright © 2015 Elsevier Ltd. All rights reserved.
Auclair, Laurent; Jambaqué, Isabelle
2015-01-01
This study addresses the relation between lexico-semantic body knowledge (i.e., body semantics) and spatial body representation (i.e., structural body representation) by analyzing naming performances as a function of body structural topography. One hundred and forty-one children ranging from 5 years 2 months to 10 years 5 months old were asked to provide a lexical label for isolated body part pictures. We compared the children's naming performances according to the location of the body parts (body parts vs. head features and also upper vs. lower limbs) or to their involvement in motor skills (distal segments, joints, and broader body parts). The results showed that the children's naming performance was better for facial body parts than for other body parts. Furthermore, it was found that the naming of body parts was better for body parts related to action. These findings suggest that the development of a spatial body representation shapes the elaboration of semantic body representation processing. Moreover, this influence was not limited to younger children. In our discussion of these results, we focus on the important role of action in the development of body representations and semantic organization.
Enhancing Biomedical Text Summarization Using Semantic Relation Extraction
Shang, Yue; Li, Yanpeng; Lin, Hongfei; Yang, Zhihao
2011-01-01
Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from multiple documents based on semantic relation extraction. Our approach includes three stages: 1) We extract semantic relations in each sentence using the semantic knowledge representation tool SemRep. 2) We develop a relation-level retrieval method to select the relations most relevant to each query concept and visualize them in a graphic representation. 3) For relations in the relevant set, we extract informative sentences that can interpret them from the document collection to generate text summary using an information retrieval based method. Our major focus in this work is to investigate the contribution of semantic relation extraction to the task of biomedical text summarization. The experimental results on summarization for a set of diseases show that the introduction of semantic knowledge improves the performance and our results are better than the MEAD system, a well-known tool for text summarization. PMID:21887336
Incorporating Semantics into Data Driven Workflows for Content Based Analysis
NASA Astrophysics Data System (ADS)
Argüello, M.; Fernandez-Prieto, M. J.
Finding meaningful associations between text elements and knowledge structures within clinical narratives in a highly verbal domain, such as psychiatry, is a challenging goal. The research presented here uses a small corpus of case histories and brings into play pre-existing knowledge, and therefore, complements other approaches that use large corpus (millions of words) and no pre-existing knowledge. The paper describes a variety of experiments for content-based analysis: Linguistic Analysis using NLP-oriented approaches, Sentiment Analysis, and Semantically Meaningful Analysis. Although it is not standard practice, the paper advocates providing automatic support to annotate the functionality as well as the data for each experiment by performing semantic annotation that uses OWL and OWL-S. Lessons learnt can be transmitted to legacy clinical databases facing the conversion of clinical narratives according to prominent Electronic Health Records standards.
A dictionary server for supplying context sensitive medical knowledge.
Ruan, W; Bürkle, T; Dudeck, J
2000-01-01
The Giessen Data Dictionary Server (GDDS), developed at Giessen University Hospital, integrates clinical systems with on-line, context sensitive medical knowledge to help with making medical decisions. By "context" we mean the clinical information that is being presented at the moment the information need is occurring. The dictionary server makes use of a semantic network supported by a medical data dictionary to link terms from clinical applications to their proper information sources. It has been designed to analyze the network structure itself instead of knowing the layout of the semantic net in advance. This enables us to map appropriate information sources to various clinical applications, such as nursing documentation, drug prescription and cancer follow up systems. This paper describes the function of the dictionary server and shows how the knowledge stored in the semantic network is used in the dictionary service.
NASA Astrophysics Data System (ADS)
Narock, T.; Arko, R. A.; Carbotte, S. M.; Chandler, C. L.; Cheatham, M.; Finin, T.; Hitzler, P.; Krisnadhi, A.; Raymond, L. M.; Shepherd, A.; Wiebe, P. H.
2014-12-01
A wide spectrum of maturing methods and tools, collectively characterized as the Semantic Web, is helping to vastly improve the dissemination of scientific research. Creating semantic integration requires input from both domain and cyberinfrastructure scientists. OceanLink, an NSF EarthCube Building Block, is demonstrating semantic technologies through the integration of geoscience data repositories, library holdings, conference abstracts, and funded research awards. Meeting project objectives involves applying semantic technologies to support data representation, discovery, sharing and integration. Our semantic cyberinfrastructure components include ontology design patterns, Linked Data collections, semantic provenance, and associated services to enhance data and knowledge discovery, interoperation, and integration. We discuss how these components are integrated, the continued automated and semi-automated creation of semantic metadata, and techniques we have developed to integrate ontologies, link resources, and preserve provenance and attribution.
The Semantic eScience Framework
NASA Astrophysics Data System (ADS)
McGuinness, Deborah; Fox, Peter; Hendler, James
2010-05-01
The goal of this effort is to design and implement a configurable and extensible semantic eScience framework (SESF). Configuration requires research into accommodating different levels of semantic expressivity and user requirements from use cases. Extensibility is being achieved in a modular approach to the semantic encodings (i.e. ontologies) performed in community settings, i.e. an ontology framework into which specific applications all the way up to communities can extend the semantics for their needs.We report on how we are accommodating the rapid advances in semantic technologies and tools and the sustainable software path for the future (certain) technical advances. In addition to a generalization of the current data science interface, we will present plans for an upper-level interface suitable for use by clearinghouses, and/or educational portals, digital libraries, and other disciplines.SESF builds upon previous work in the Virtual Solar-Terrestrial Observatory. The VSTO utilizes leading edge knowledge representation, query and reasoning techniques to support knowledge-enhanced search, data access, integration, and manipulation. It encodes term meanings and their inter-relationships in ontologies anduses these ontologies and associated inference engines to semantically enable the data services. The Semantically-Enabled Science Data Integration (SESDI) project implemented data integration capabilities among three sub-disciplines; solar radiation, volcanic outgassing and atmospheric structure using extensions to existingmodular ontolgies and used the VSTO data framework, while adding smart faceted search and semantic data registrationtools. The Semantic Provenance Capture in Data Ingest Systems (SPCDIS) has added explanation provenance capabilities to an observational data ingest pipeline for images of the Sun providing a set of tools to answer diverseend user questions such as ``Why does this image look bad?. http://tw.rpi.edu/portal/SESF
The Semantic eScience Framework
NASA Astrophysics Data System (ADS)
Fox, P. A.; McGuinness, D. L.
2009-12-01
The goal of this effort is to design and implement a configurable and extensible semantic eScience framework (SESF). Configuration requires research into accommodating different levels of semantic expressivity and user requirements from use cases. Extensibility is being achieved in a modular approach to the semantic encodings (i.e. ontologies) performed in community settings, i.e. an ontology framework into which specific applications all the way up to communities can extend the semantics for their needs.We report on how we are accommodating the rapid advances in semantic technologies and tools and the sustainable software path for the future (certain) technical advances. In addition to a generalization of the current data science interface, we will present plans for an upper-level interface suitable for use by clearinghouses, and/or educational portals, digital libraries, and other disciplines.SESF builds upon previous work in the Virtual Solar-Terrestrial Observatory. The VSTO utilizes leading edge knowledge representation, query and reasoning techniques to support knowledge-enhanced search, data access, integration, and manipulation. It encodes term meanings and their inter-relationships in ontologies anduses these ontologies and associated inference engines to semantically enable the data services. The Semantically-Enabled Science Data Integration (SESDI) project implemented data integration capabilities among three sub-disciplines; solar radiation, volcanic outgassing and atmospheric structure using extensions to existingmodular ontolgies and used the VSTO data framework, while adding smart faceted search and semantic data registrationtools. The Semantic Provenance Capture in Data Ingest Systems (SPCDIS) has added explanation provenance capabilities to an observational data ingest pipeline for images of the Sun providing a set of tools to answer diverseend user questions such as ``Why does this image look bad?.
Rice, Grace E; Caswell, Helen; Moore, Perry; Lambon Ralph, Matthew A; Hoffman, Paul
2018-06-06
One critical feature of any well-engineered system is its resilience to perturbation and minor damage. The purpose of the current study was to investigate how resilience is achieved in higher cognitive systems, which we explored through the domain of semantic cognition. Convergent evidence implicates the bilateral anterior temporal lobes (ATLs) as a conceptual knowledge hub. While bilateral damage to this region produces profound semantic impairment, unilateral atrophy/resection or transient perturbation has a limited effect. Two neural mechanisms might underpin this resilience to unilateral ATL damage: 1) the undamaged ATL upregulates its activation in order to compensate; and/or 2) prefrontal regions involved in control of semantic retrieval upregulate to compensate for the impoverished semantic representations that follow from ATL damage. To test these possibilities, 34 postsurgical temporal lobe epilepsy patients and 20 age-matched controls were scanned whilst completing semantic tasks. Pictorial tasks, which produced bilateral frontal and temporal activation, showed few activation differences between patients and control participants. Written word tasks, however, produced a left-lateralized activation pattern and greater differences between the groups. Patients with right ATL resection increased activation in left inferior frontal gyrus (IFG). Patients with left ATL resection upregulated both the right ATL and right IFG. Consistent with recent computational models, these results indicate that 1) written word semantic processing in patients with ATL resection is supported by upregulation of semantic knowledge and control regions, principally in the undamaged hemisphere, and 2) pictorial semantic processing is less affected, presumably because it draws on a more bilateral network.
Löfkvist, Ulrika; Almkvist, Ove; Lyxell, Björn; Tallberg, Ing-Mari
2014-02-01
Lexical-semantic ability was investigated among children aged 6-9 years with cochlear implants (CI) and compared to clinical groups of children with language impairment (LI) and autism spectrum disorder (ASD) as well as to age-matched children with normal hearing (NH). In addition, the influence of age at implantation on lexical-semantic ability was investigated among children with CI. 97 children divided into four groups participated, CI (n=34), LI (n=12), ASD (n=12), and NH (n=39). A battery of tests, including picture naming, receptive vocabulary and knowledge of semantic features, was used for assessment. A semantic response analysis of the erroneous responses on the picture-naming test was also performed. The group of children with CI exhibited a naming ability comparable to that of the age-matched children with NH, and they also possessed a relevant semantic knowledge of certain words that they were unable to name correctly. Children with CI had a significantly better understanding of words compared to the children with LI and ASD, but a worse understanding than those with NH. The significant differences between groups remained after controlling for age and non-verbal cognitive ability. The children with CI demonstrated lexical-semantic abilities comparable to age-matched children with NH, while children with LI and ASD had a more atypical lexical-semantic profile and poorer sizes of expressive and receptive vocabularies. Dissimilar causes of neurodevelopmental processes seemingly affected lexical-semantic abilities in different ways in the clinical groups. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Creating personalised clinical pathways by semantic interoperability with electronic health records.
Wang, Hua-Qiong; Li, Jing-Song; Zhang, Yi-Fan; Suzuki, Muneou; Araki, Kenji
2013-06-01
There is a growing realisation that clinical pathways (CPs) are vital for improving the treatment quality of healthcare organisations. However, treatment personalisation is one of the main challenges when implementing CPs, and the inadequate dynamic adaptability restricts the practicality of CPs. The purpose of this study is to improve the practicality of CPs using semantic interoperability between knowledge-based CPs and semantic electronic health records (EHRs). Simple protocol and resource description framework query language is used to gather patient information from semantic EHRs. The gathered patient information is entered into the CP ontology represented by web ontology language. Then, after reasoning over rules described by semantic web rule language in the Jena semantic framework, we adjust the standardised CPs to meet different patients' practical needs. A CP for acute appendicitis is used as an example to illustrate how to achieve CP customisation based on the semantic interoperability between knowledge-based CPs and semantic EHRs. A personalised care plan is generated by comprehensively analysing the patient's personal allergy history and past medical history, which are stored in semantic EHRs. Additionally, by monitoring the patient's clinical information, an exception is recorded and handled during CP execution. According to execution results of the actual example, the solutions we present are shown to be technically feasible. This study contributes towards improving the clinical personalised practicality of standardised CPs. In addition, this study establishes the foundation for future work on the research and development of an independent CP system. Copyright © 2013 Elsevier B.V. All rights reserved.
Griffon, N; Charlet, J; Darmoni, Sj
2013-01-01
To summarize the best papers in the field of Knowledge Representation and Management (KRM). A synopsis of the four selected articles for the IMIA Yearbook 2013 KRM section is provided, as well as highlights of current KRM trends, in particular, of the semantic web in daily health practice. The manual selection was performed in three stages: first a set of 3,106 articles, then a second set of 86 articles followed by a third set of 15 articles, and finally the last set of four chosen articles. Among the four selected articles (see Table 1), one focuses on knowledge engineering to prevent adverse drug events; the objective of the second is to propose mappings between clinical archetypes and SNOMED CT in the context of clinical practice; the third presents an ontology to create a question-answering system; the fourth describes a biomonitoring network based on semantic web technologies. These four articles clearly indicate that the health semantic web has become a part of daily practice of health professionals since 2012. In the review of the second set of 86 articles, the same topics included in the previous IMIA yearbook remain active research fields: Knowledge extraction, automatic indexing, information retrieval, natural language processing, management of health terminologies and ontologies.
NASA Astrophysics Data System (ADS)
Maksimov, N. V.; Tikhomirov, G. V.; Golitsyna, O. L.
2017-01-01
The main problems and circumstances that influence the processes of creating effective knowledge management systems were described. These problems particularly include high species diversity of instruments for knowledge representation, lack of adequate lingware, including formal representation of semantic relationships. For semantic data descriptions development a conceptual model of the subject area and a conceptual-lexical system should be designed on proposals of ISO-15926 standard. It is proposed to conduct an information integration of educational and production processes on the basis of information systems technologies. Integrated knowledge management system information environment combines both traditional information resources and specific information resources of subject domain including task context and implicit/tacit knowledge.
Handling knowledge via Concept Maps: a space weather use case
NASA Astrophysics Data System (ADS)
Messerotti, Mauro; Fox, Peter
Concept Maps (Cmaps) are powerful means for knowledge coding in graphical form. As flexible software tools exist to manipulate the knowledge embedded in Cmaps in machine-readable form, such complex entities are suitable candidates not only for the representation of ontologies and semantics in Virtual Observatory (VO) architectures, but also for knowledge handling and knowledge discovery. In this work, we present a use case relevant to space weather applications and we elaborate on its possible implementation and adavanced use in Semantic Virtual Observatories dedicated to Sun-Earth Connections. This analysis was carried out in the framework of the Electronic Geophysical Year (eGY) and represents an achievement synergized by the eGY Virtual Observatories Working Group.
Formal ontologies in biomedical knowledge representation.
Schulz, S; Jansen, L
2013-01-01
Medical decision support and other intelligent applications in the life sciences depend on increasing amounts of digital information. Knowledge bases as well as formal ontologies are being used to organize biomedical knowledge and data. However, these two kinds of artefacts are not always clearly distinguished. Whereas the popular RDF(S) standard provides an intuitive triple-based representation, it is semantically weak. Description logics based ontology languages like OWL-DL carry a clear-cut semantics, but they are computationally expensive, and they are often misinterpreted to encode all kinds of statements, including those which are not ontological. We distinguish four kinds of statements needed to comprehensively represent domain knowledge: universal statements, terminological statements, statements about particulars and contingent statements. We argue that the task of formal ontologies is solely to represent universal statements, while the non-ontological kinds of statements can nevertheless be connected with ontological representations. To illustrate these four types of representations, we use a running example from parasitology. We finally formulate recommendations for semantically adequate ontologies that can efficiently be used as a stable framework for more context-dependent biomedical knowledge representation and reasoning applications like clinical decision support systems.
EliXR-TIME: A Temporal Knowledge Representation for Clinical Research Eligibility Criteria.
Boland, Mary Regina; Tu, Samson W; Carini, Simona; Sim, Ida; Weng, Chunhua
2012-01-01
Effective clinical text processing requires accurate extraction and representation of temporal expressions. Multiple temporal information extraction models were developed but a similar need for extracting temporal expressions in eligibility criteria (e.g., for eligibility determination) remains. We identified the temporal knowledge representation requirements of eligibility criteria by reviewing 100 temporal criteria. We developed EliXR-TIME, a frame-based representation designed to support semantic annotation for temporal expressions in eligibility criteria by reusing applicable classes from well-known clinical temporal knowledge representations. We used EliXR-TIME to analyze a training set of 50 new temporal eligibility criteria. We evaluated EliXR-TIME using an additional random sample of 20 eligibility criteria with temporal expressions that have no overlap with the training data, yielding 92.7% (76 / 82) inter-coder agreement on sentence chunking and 72% (72 / 100) agreement on semantic annotation. We conclude that this knowledge representation can facilitate semantic annotation of the temporal expressions in eligibility criteria.
Semantic technologies in a decision support system
NASA Astrophysics Data System (ADS)
Wasielewska, K.; Ganzha, M.; Paprzycki, M.; Bǎdicǎ, C.; Ivanovic, M.; Lirkov, I.
2015-10-01
The aim of our work is to design a decision support system based on ontological representation of domain(s) and semantic technologies. Specifically, we consider the case when Grid / Cloud user describes his/her requirements regarding a "resource" as a class expression from an ontology, while the instances of (the same) ontology represent available resources. The goal is to help the user to find the best option with respect to his/her requirements, while remembering that user's knowledge may be "limited." In this context, we discuss multiple approaches based on semantic data processing, which involve different "forms" of user interaction with the system. Specifically, we consider: (a) ontological matchmaking based on SPARQL queries and class expression, (b) graph-based semantic closeness of instances representing user requirements (constructed from the class expression) and available resources, and (c) multicriterial analysis based on the AHP method, which utilizes expert domain knowledge (also ontologically represented).
Model for Semantically Rich Point Cloud Data
NASA Astrophysics Data System (ADS)
Poux, F.; Neuville, R.; Hallot, P.; Billen, R.
2017-10-01
This paper proposes an interoperable model for managing high dimensional point clouds while integrating semantics. Point clouds from sensors are a direct source of information physically describing a 3D state of the recorded environment. As such, they are an exhaustive representation of the real world at every scale: 3D reality-based spatial data. Their generation is increasingly fast but processing routines and data models lack of knowledge to reason from information extraction rather than interpretation. The enhanced smart point cloud developed model allows to bring intelligence to point clouds via 3 connected meta-models while linking available knowledge and classification procedures that permits semantic injection. Interoperability drives the model adaptation to potentially many applications through specialized domain ontologies. A first prototype is implemented in Python and PostgreSQL database and allows to combine semantic and spatial concepts for basic hybrid queries on different point clouds.
SemanticOrganizer: A Customizable Semantic Repository for Distributed NASA Project Teams
NASA Technical Reports Server (NTRS)
Keller, Richard M.; Berrios, Daniel C.; Carvalho, Robert E.; Hall, David R.; Rich, Stephen J.; Sturken, Ian B.; Swanson, Keith J.; Wolfe, Shawn R.
2004-01-01
SemanticOrganizer is a collaborative knowledge management system designed to support distributed NASA projects, including diverse teams of scientists, engineers, and accident investigators. The system provides a customizable, semantically structured information repository that stores work products relevant to multiple projects of differing types. SemanticOrganizer is one of the earliest and largest semantic web applications deployed at NASA to date, and has been used in diverse contexts ranging from the investigation of Space Shuttle Columbia's accident to the search for life on other planets. Although the underlying repository employs a single unified ontology, access control and ontology customization mechanisms make the repository contents appear different for each project team. This paper describes SemanticOrganizer, its customization facilities, and a sampling of its applications. The paper also summarizes some key lessons learned from building and fielding a successful semantic web application across a wide-ranging set of domains with diverse users.
Centrality-based Selection of Semantic Resources for Geosciences
NASA Astrophysics Data System (ADS)
Cerba, Otakar; Jedlicka, Karel
2017-04-01
Semantical questions intervene almost in all disciplines dealing with geographic data and information, because relevant semantics is crucial for any way of communication and interaction among humans as well as among machines. But the existence of such a large number of different semantic resources (such as various thesauri, controlled vocabularies, knowledge bases or ontologies) makes the process of semantics implementation much more difficult and complicates the use of the advantages of semantics. This is because in many cases users are not able to find the most suitable resource for their purposes. The research presented in this paper introduces a methodology consisting of an analysis of identical relations in Linked Data space, which covers a majority of semantic resources, to find a suitable resource of semantic information. Identical links interconnect representations of an object or a concept in various semantic resources. Therefore this type of relations is considered to be crucial from the view of Linked Data, because these links provide new additional information, including various views on one concept based on different cultural or regional aspects (so-called social role of Linked Data). For these reasons it is possible to declare that one reasonable criterion for feasible semantic resources for almost all domains, including geosciences, is their position in a network of interconnected semantic resources and level of linking to other knowledge bases and similar products. The presented methodology is based on searching of mutual connections between various instances of one concept using "follow your nose" approach. The extracted data on interconnections between semantic resources are arranged to directed graphs and processed by various metrics patterned on centrality computing (degree, closeness or betweenness centrality). Semantic resources recommended by the research could be used for providing semantically described keywords for metadata records or as names of items in data models. Such an approach enables much more efficient data harmonization, integration, sharing and exploitation. * * * * This publication was supported by the project LO1506 of the Czech Ministry of Education, Youth and Sports. This publication was supported by project Data-Driven Bioeconomy (DataBio) from the ICT-15-2016-2017, Big Data PPP call.
Nonconscious semantic processing of emotional words modulates conscious access
Gaillard, Raphaël; Del Cul, Antoine; Naccache, Lionel; Vinckier, Fabien; Cohen, Laurent; Dehaene, Stanislas
2006-01-01
Whether masked words can be processed at a semantic level remains a controversial issue in cognitive psychology. Although recent behavioral studies have demonstrated masked semantic priming for number words, attempts to generalize this finding to other categories of words have failed. Here, as an alternative to subliminal priming, we introduce a sensitive behavioral method to detect nonconscious semantic processing of words. The logic of this method consists of presenting words close to the threshold for conscious perception and examining whether their semantic content modulates performance in objective and subjective tasks. Our results disclose two independent sources of modulation of the threshold for access to consciousness. First, prior conscious perception of words increases the detection rate of the same words when they are subsequently presented with stronger masking. Second, the threshold for conscious access is lower for emotional words than for neutral ones, even for words that have not been previously consciously perceived, thus implying that written words can receive nonconscious semantic processing. PMID:16648261
ERIC Educational Resources Information Center
LoGerfo, Emanuele; Oliveri, Massimiliano; Torriero, Sara; Salerno, Silvia; Koch, Giacomo; Caltagirone, Carlo
2008-01-01
We investigated the differential role of two frontal regions in the processing of grammatical and semantic knowledge. Given the documented specificity of the prefrontal cortex for the grammatical class of verbs, and of the primary motor cortex for the semantic class of action words, we sought to investigate whether the prefrontal cortex is also…
NASA Technical Reports Server (NTRS)
Campbell, William J.; Short, Nicholas M., Jr.; Roelofs, Larry H.; Dorfman, Erik
1991-01-01
A methodology for optimizing organization of data obtained by NASA earth and space missions is discussed. The methodology uses a concept based on semantic data modeling techniques implemented in a hierarchical storage model. The modeling is used to organize objects in mass storage devices, relational database systems, and object-oriented databases. The semantic data modeling at the metadata record level is examined, including the simulation of a knowledge base and semantic metadata storage issues. The semantic data model hierarchy and its application for efficient data storage is addressed, as is the mapping of the application structure to the mass storage.
Modulation of alpha oscillations is required for the suppression of semantic interference.
Melnik, Natalia; Mapelli, Igor; Özkurt, Tolga Esat
2017-10-01
Recent findings on alpha band oscillations suggest their important role in memory consolidation and suppression of external distractors such as environmental noise. However, less attention was given to the phenomenon of internal distracting information being solely inherent to the stimuli content. Human memory may be prone to internal distractions caused by semantic relatedness between the meaning of words (e.g., atom, neutron, nucleus, etc.) to be encoded, i.e., semantic interference. Our study investigates the brain oscillatory dynamics behind the semantic interference phenomenon, whose possible outcome is known as false memories. In this direction, Deese-Roediger-McDermott word lists were appropriated for a modified Sternberg paradigm in auditory modality. Participants received semantically related and unrelated word lists via headphones while EEG data were acquired. Semantic interference triggered the false memory rates to be higher than those of other types of memory errors. Analysis demonstrated that the upper part of alpha band (∼10-12Hz) power decreases on parieto-occipital channels in the retention interval, prior to the probe item for semantically related condition. Our study elucidates the oscillatory mechanisms behind semantic interference by relying on alpha functional inhibition theory. Copyright © 2017 Elsevier Inc. All rights reserved.
Developing Visualization Techniques for Semantics-based Information Networks
NASA Technical Reports Server (NTRS)
Keller, Richard M.; Hall, David R.
2003-01-01
Information systems incorporating complex network structured information spaces with a semantic underpinning - such as hypermedia networks, semantic networks, topic maps, and concept maps - are being deployed to solve some of NASA s critical information management problems. This paper describes some of the human interaction and navigation problems associated with complex semantic information spaces and describes a set of new visual interface approaches to address these problems. A key strategy is to leverage semantic knowledge represented within these information spaces to construct abstractions and views that will be meaningful to the human user. Human-computer interaction methodologies will guide the development and evaluation of these approaches, which will benefit deployed NASA systems and also apply to information systems based on the emerging Semantic Web.
NASA Astrophysics Data System (ADS)
Murtazina, M. Sh; Avdeenko, T. V.
2018-05-01
The state of art and the progress in application of semantic technologies in the field of scientific and research activity have been analyzed. Even elementary empirical comparison has shown that the semantic search engines are superior in all respects to conventional search technologies. However, semantic information technologies are insufficiently used in the field of scientific and research activity in Russia. In present paper an approach to construction of ontological model of knowledge base is proposed. The ontological model is based on the upper-level ontology and the RDF mechanism for linking several domain ontologies. The ontological model is implemented in the Protégé environment.
COEUS: “semantic web in a box” for biomedical applications
2012-01-01
Background As the “omics” revolution unfolds, the growth in data quantity and diversity is bringing about the need for pioneering bioinformatics software, capable of significantly improving the research workflow. To cope with these computer science demands, biomedical software engineers are adopting emerging semantic web technologies that better suit the life sciences domain. The latter’s complex relationships are easily mapped into semantic web graphs, enabling a superior understanding of collected knowledge. Despite increased awareness of semantic web technologies in bioinformatics, their use is still limited. Results COEUS is a new semantic web framework, aiming at a streamlined application development cycle and following a “semantic web in a box” approach. The framework provides a single package including advanced data integration and triplification tools, base ontologies, a web-oriented engine and a flexible exploration API. Resources can be integrated from heterogeneous sources, including CSV and XML files or SQL and SPARQL query results, and mapped directly to one or more ontologies. Advanced interoperability features include REST services, a SPARQL endpoint and LinkedData publication. These enable the creation of multiple applications for web, desktop or mobile environments, and empower a new knowledge federation layer. Conclusions The platform, targeted at biomedical application developers, provides a complete skeleton ready for rapid application deployment, enhancing the creation of new semantic information systems. COEUS is available as open source at http://bioinformatics.ua.pt/coeus/. PMID:23244467
COEUS: "semantic web in a box" for biomedical applications.
Lopes, Pedro; Oliveira, José Luís
2012-12-17
As the "omics" revolution unfolds, the growth in data quantity and diversity is bringing about the need for pioneering bioinformatics software, capable of significantly improving the research workflow. To cope with these computer science demands, biomedical software engineers are adopting emerging semantic web technologies that better suit the life sciences domain. The latter's complex relationships are easily mapped into semantic web graphs, enabling a superior understanding of collected knowledge. Despite increased awareness of semantic web technologies in bioinformatics, their use is still limited. COEUS is a new semantic web framework, aiming at a streamlined application development cycle and following a "semantic web in a box" approach. The framework provides a single package including advanced data integration and triplification tools, base ontologies, a web-oriented engine and a flexible exploration API. Resources can be integrated from heterogeneous sources, including CSV and XML files or SQL and SPARQL query results, and mapped directly to one or more ontologies. Advanced interoperability features include REST services, a SPARQL endpoint and LinkedData publication. These enable the creation of multiple applications for web, desktop or mobile environments, and empower a new knowledge federation layer. The platform, targeted at biomedical application developers, provides a complete skeleton ready for rapid application deployment, enhancing the creation of new semantic information systems. COEUS is available as open source at http://bioinformatics.ua.pt/coeus/.
fMRI evidence of equivalent neural suppression by repetition and prior knowledge.
Poppenk, J; McIntosh, A R; Moscovitch, M
2016-09-01
Stimulus repetition speeds behavioral responding (behavioral priming) and is accompanied by suppressed neural responses (repetition suppression; RS) that have been observed up to three days after initial exposure. While some proposals have suggested the two phenomena are linked, behavioral priming has been observed many years after initial exposure, whereas RS is widely considered a transitory phenomenon. This raises the question: what is the true upper limit of RS persistence? To answer this question, we scanned healthy, English-native adults with fMRI as they viewed novel (Asian) proverbs, recently repeated (Asian) proverbs, and previously known (English) proverbs that were matched on various dimensions. We then estimated RS by comparing repeated or previously known proverbs against novel ones. Multivariate analyses linked previously known and repeated proverbs with statistically indistinguishable RS in a broad visual-linguistic network. In each suppressed region, prior knowledge and repetition also induced a common shift in functional connectivity, further underscoring the similarity of the RS phenomenon induced by these conditions. By contrast, activated regions readily distinguished prior knowledge and repetition conditions in a manner consistent with engagement of semantic and episodic memory systems, respectively. Our results illustrate that regardless of whether RS is understood in terms of its magnitude, spatial extent or functional connectivity profile, typical RS effects can be elicited even under conditions where recently triggered biological processes or episodic memory are unlikely to play a prominent role. These results provide important new evidence that RS (of the kind observed after an interval of at least several minutes) reflects the facilitation of perceptual and comprehension processes by any type of information retrieved from long-term memory. Copyright © 2016 Elsevier Ltd. All rights reserved.
ERIC Educational Resources Information Center
Liu, Hongyan; Hu, Zhiguo; Peng, Danling; Yang, Yanhui; Li, Kuncheng
2010-01-01
The brain activity associated with automatic semantic priming has been extensively studied. Thus far there has been no prior study that directly contrasts the neural mechanisms of semantic and affective priming. The present study employed event-related fMRI to examine the common and distinct neural bases underlying conceptual and affective priming…
Bagley, Amy D.; Abramowitz, Carolyn S.; Kosson, David S.
2010-01-01
Deficits in emotion processing have been widely reported to be central to psychopathy. However, few prior studies have examined vocal affect recognition in psychopaths, and these studies suffer from significant methodological limitations. Moreover, prior studies have yielded conflicting findings regarding the specificity of psychopaths’ affect recognition deficits. This study examined vocal affect recognition in 107 male inmates under conditions requiring isolated prosodic vs. semantic analysis of affective cues and compared subgroups of offenders identified via cluster analysis on vocal affect recognition. Psychopaths demonstrated deficits in vocal affect recognition under conditions requiring use of semantic cues and conditions requiring use of prosodic cues. Moreover, both primary and secondary psychopaths exhibited relatively similar emotional deficits in the semantic analysis condition compared to nonpsychopathic control participants. This study demonstrates that psychopaths’ vocal affect recognition deficits are not due to methodological limitations of previous studies and provides preliminary evidence that primary and secondary psychopaths exhibit generally similar deficits in vocal affect recognition. PMID:19413412
Taxonomic and thematic organisation of proper name conceptual knowledge.
Crutch, Sebastian J; Warrington, Elizabeth K
2011-01-01
We report the investigation of the organisation of proper names in two aphasic patients (NBC and FBI). The performance of both patients on spoken word to written word matching tasks was inconsistent, affected by presentation rate and semantic relatedness of the competing responses, all hallmarks of a refractory semantic access dysphasia. In a series of experiments we explored the semantic relatedness effects within their proper name vocabulary, including brand names and person names. First we demonstrated the interaction between very fine grain organisation and personal experience, with one patient with a special interest in the cinema demonstrating higher error rates when identifying the names of actors working in a similar film genre (e.g., action movies: Arnold Schwarzenegger, Bruce Willis, Sylvester Stallone, Mel Gibson) than those working in different genres (e.g., Arnold Schwarzenegger, Gregory Peck, Robin Williams, Gene Kelly). Second we compared directly two potential principles of semantic organisation - taxonomic and thematic. Furthermore we considered these principles of organisation in the context of the individuals' personal knowledge base. We selected topics matching the interests and experience of each patient, namely cinema and literature (NBC) and naval history (FBI). The stimulus items were arranged in taxonomic arrays (e.g., Jane Austen, Emily Bronte, Agatha Christie), thematic arrays (e.g., Jane Austen, Pride and Prejudice, Mr Darcy), and unrelated arrays (e.g., Jane Austen, Wuthering Heights, Hercule Poirot). We documented that different patterns of taxonomic and thematic organisation were constrained by whether the individual has limited knowledge, moderate knowledge or detailed knowledge of a particular vocabulary. It is suggested that moderate proper name knowledge is primarily organised by taxonomy whereas extensive experience results in a more detailed knowledge base in which theme is a powerful organising principle.
Taxonomic and Thematic Organisation of Proper Name Conceptual Knowledge
Crutch, Sebastian J.; Warrington, Elizabeth K.
2011-01-01
We report the investigation of the organisation of proper names in two aphasic patients (NBC and FBI). The performance of both patients on spoken word to written word matching tasks was inconsistent, affected by presentation rate and semantic relatedness of the competing responses, all hallmarks of a refractory semantic access dysphasia. In a series of experiments we explored the semantic relatedness effects within their proper name vocabulary, including brand names and person names. First we demonstrated the interaction between very fine grain organisation and personal experience, with one patient with a special interest in the cinema demonstrating higher error rates when identifying the names of actors working in a similar film genre (e.g. action movies: Arnold Schwarzenegger, Bruce Willis, Sylvester Stallone, Mel Gibson) than those working in different genres (e.g. Arnold Schwarzenegger, Gregory Peck, Robin Williams, Gene Kelly). Second we compared directly two potential principles of semantic organisation – taxonomic and thematic. Furthermore we considered these principles of organisation in the context of the individuals' personal knowledge base. We selected topics matching the interests and experience of each patient, namely cinema and literature (NBC) and naval history (FBI). The stimulus items were arranged in taxonomic arrays (e.g. Jane Austen, Emily Bronte, Agatha Christie), thematic arrays (e.g. Jane Austen, Pride and Prejudice, Mr Darcy), and unrelated arrays (e.g. Jane Austen, Wuthering Heights, Hercule Poirot). We documented that different patterns of taxonomic and thematic organisation were constrained by whether the individual has limited knowledge, moderate knowledge or detailed knowledge of a particular vocabulary. It is suggested that moderate proper name knowledge is primarily organised by taxonomy whereas extensive experience results in a more detailed knowledge base in which theme is a powerful organising principle. PMID:22063815
Yap, Melvin J.; Tse, Chi-Shing; Balota, David A.
2009-01-01
Word frequency and semantic priming effects are among the most robust effects in visual word recognition, and it has been generally assumed that these two variables produce interactive effects in lexical decision performance, with larger priming effects for low-frequency targets. The results from four lexical decision experiments indicate that the joint effects of semantic priming and word frequency are critically dependent upon differences in the vocabulary knowledge of the participants. Specifically, across two Universities, additive effects of the two variables were observed in participants with more vocabulary knowledge, while interactive effects were observed in participants with less vocabulary knowledge. These results are discussed with reference to Borowsky and Besner’s (1993) multistage account and Plaut and Booth’s (2000) single-mechanism model. In general, the findings are also consistent with a flexible lexical processing system that optimizes performance based on processing fluency and task demands. PMID:20161653
Knowledge Extraction and Semantic Annotation of Text from the Encyclopedia of Life
Thessen, Anne E.; Parr, Cynthia Sims
2014-01-01
Numerous digitization and ontological initiatives have focused on translating biological knowledge from narrative text to machine-readable formats. In this paper, we describe two workflows for knowledge extraction and semantic annotation of text data objects featured in an online biodiversity aggregator, the Encyclopedia of Life. One workflow tags text with DBpedia URIs based on keywords. Another workflow finds taxon names in text using GNRD for the purpose of building a species association network. Both workflows work well: the annotation workflow has an F1 Score of 0.941 and the association algorithm has an F1 Score of 0.885. Existing text annotators such as Terminizer and DBpedia Spotlight performed well, but require some optimization to be useful in the ecology and evolution domain. Important future work includes scaling up and improving accuracy through the use of distributional semantics. PMID:24594988
A dictionary server for supplying context sensitive medical knowledge.
Ruan, W.; Bürkle, T.; Dudeck, J.
2000-01-01
The Giessen Data Dictionary Server (GDDS), developed at Giessen University Hospital, integrates clinical systems with on-line, context sensitive medical knowledge to help with making medical decisions. By "context" we mean the clinical information that is being presented at the moment the information need is occurring. The dictionary server makes use of a semantic network supported by a medical data dictionary to link terms from clinical applications to their proper information sources. It has been designed to analyze the network structure itself instead of knowing the layout of the semantic net in advance. This enables us to map appropriate information sources to various clinical applications, such as nursing documentation, drug prescription and cancer follow up systems. This paper describes the function of the dictionary server and shows how the knowledge stored in the semantic network is used in the dictionary service. PMID:11079978
Socio-contextual Network Mining for User Assistance in Web-based Knowledge Gathering Tasks
NASA Astrophysics Data System (ADS)
Rajendran, Balaji; Kombiah, Iyakutti
Web-based Knowledge Gathering (WKG) is a specialized and complex information seeking task carried out by many users on the web, for their various learning, and decision-making requirements. We construct a contextual semantic structure by observing the actions of the users involved in WKG task, in order to gain an understanding of their task and requirement. We also build a knowledge warehouse in the form of a master Semantic Link Network (SLX) that accommodates and assimilates all the contextual semantic structures. This master SLX, which is a socio-contextual network, is then mined to provide contextual inputs to the current users through their agents. We validated our approach through experiments and analyzed the benefits to the users in terms of resource explorations and the time saved. The results are positive enough to motivate us to implement in a larger scale.
The neural and computational bases of semantic cognition.
Ralph, Matthew A Lambon; Jefferies, Elizabeth; Patterson, Karalyn; Rogers, Timothy T
2017-01-01
Semantic cognition refers to our ability to use, manipulate and generalize knowledge that is acquired over the lifespan to support innumerable verbal and non-verbal behaviours. This Review summarizes key findings and issues arising from a decade of research into the neurocognitive and neurocomputational underpinnings of this ability, leading to a new framework that we term controlled semantic cognition (CSC). CSC offers solutions to long-standing queries in philosophy and cognitive science, and yields a convergent framework for understanding the neural and computational bases of healthy semantic cognition and its dysfunction in brain disorders.
A DNA-based semantic fusion model for remote sensing data.
Sun, Heng; Weng, Jian; Yu, Guangchuang; Massawe, Richard H
2013-01-01
Semantic technology plays a key role in various domains, from conversation understanding to algorithm analysis. As the most efficient semantic tool, ontology can represent, process and manage the widespread knowledge. Nowadays, many researchers use ontology to collect and organize data's semantic information in order to maximize research productivity. In this paper, we firstly describe our work on the development of a remote sensing data ontology, with a primary focus on semantic fusion-driven research for big data. Our ontology is made up of 1,264 concepts and 2,030 semantic relationships. However, the growth of big data is straining the capacities of current semantic fusion and reasoning practices. Considering the massive parallelism of DNA strands, we propose a novel DNA-based semantic fusion model. In this model, a parallel strategy is developed to encode the semantic information in DNA for a large volume of remote sensing data. The semantic information is read in a parallel and bit-wise manner and an individual bit is converted to a base. By doing so, a considerable amount of conversion time can be saved, i.e., the cluster-based multi-processes program can reduce the conversion time from 81,536 seconds to 4,937 seconds for 4.34 GB source data files. Moreover, the size of result file recording DNA sequences is 54.51 GB for parallel C program compared with 57.89 GB for sequential Perl. This shows that our parallel method can also reduce the DNA synthesis cost. In addition, data types are encoded in our model, which is a basis for building type system in our future DNA computer. Finally, we describe theoretically an algorithm for DNA-based semantic fusion. This algorithm enables the process of integration of the knowledge from disparate remote sensing data sources into a consistent, accurate, and complete representation. This process depends solely on ligation reaction and screening operations instead of the ontology.
A DNA-Based Semantic Fusion Model for Remote Sensing Data
Sun, Heng; Weng, Jian; Yu, Guangchuang; Massawe, Richard H.
2013-01-01
Semantic technology plays a key role in various domains, from conversation understanding to algorithm analysis. As the most efficient semantic tool, ontology can represent, process and manage the widespread knowledge. Nowadays, many researchers use ontology to collect and organize data's semantic information in order to maximize research productivity. In this paper, we firstly describe our work on the development of a remote sensing data ontology, with a primary focus on semantic fusion-driven research for big data. Our ontology is made up of 1,264 concepts and 2,030 semantic relationships. However, the growth of big data is straining the capacities of current semantic fusion and reasoning practices. Considering the massive parallelism of DNA strands, we propose a novel DNA-based semantic fusion model. In this model, a parallel strategy is developed to encode the semantic information in DNA for a large volume of remote sensing data. The semantic information is read in a parallel and bit-wise manner and an individual bit is converted to a base. By doing so, a considerable amount of conversion time can be saved, i.e., the cluster-based multi-processes program can reduce the conversion time from 81,536 seconds to 4,937 seconds for 4.34 GB source data files. Moreover, the size of result file recording DNA sequences is 54.51 GB for parallel C program compared with 57.89 GB for sequential Perl. This shows that our parallel method can also reduce the DNA synthesis cost. In addition, data types are encoded in our model, which is a basis for building type system in our future DNA computer. Finally, we describe theoretically an algorithm for DNA-based semantic fusion. This algorithm enables the process of integration of the knowledge from disparate remote sensing data sources into a consistent, accurate, and complete representation. This process depends solely on ligation reaction and screening operations instead of the ontology. PMID:24116207
Leek, E Charles; d'Avossa, Giovanni; Tainturier, Marie-Josèphe; Roberts, Daniel J; Yuen, Sung Lai; Hu, Mo; Rafal, Robert
2012-01-01
This study examines how brain damage can affect the cognitive processes that support the integration of sensory input and prior knowledge during shape perception. It is based on the first detailed study of acquired ventral simultanagnosia, which was found in a patient (M.T.) with posterior occipitotemporal lesions encompassing V4 bilaterally. Despite showing normal object recognition for single items in both accuracy and response times (RTs), and intact low-level vision assessed across an extensive battery of tests, M.T. was impaired in object identification with overlapping figures displays. Task performance was modulated by familiarity: Unlike controls, M.T. was faster with overlapping displays of abstract shapes than with overlapping displays of common objects. His performance with overlapping common object displays was also influenced by both the semantic relatedness and visual similarity of the display items. These findings challenge claims that visual perception is driven solely by feedforward mechanisms and show how brain damage can selectively impair high-level perceptual processes supporting the integration of stored knowledge and visual sensory input.
Soualmia, L F; Charlet, J
2016-11-10
To summarize excellent current research in the field of Knowledge Representation and Management (KRM) within the health and medical care domain. We provide a synopsis of the 2016 IMIA selected articles as well as a related synthetic overview of the current and future field activities. A first step of the selection was performed through MEDLINE querying with a list of MeSH descriptors completed by a list of terms adapted to the KRM section. The second step of the selection was completed by the two section editors who separately evaluated the set of 1,432 articles. The third step of the selection consisted of a collective work that merged the evaluation results to retain 15 articles for peer-review. The selection and evaluation process of this Yearbook's section on Knowledge Representation and Management has yielded four excellent and interesting articles regarding semantic interoperability for health care by gathering heterogeneous sources (knowledge and data) and auditing ontologies. In the first article, the authors present a solution based on standards and Semantic Web technologies to access distributed and heterogeneous datasets in the domain of breast cancer clinical trials. The second article describes a knowledge-based recommendation system that relies on ontologies and Semantic Web rules in the context of chronic diseases dietary. The third article is related to concept-recognition and text-mining to derive common human diseases model and a phenotypic network of common diseases. In the fourth article, the authors highlight the need for auditing the SNOMED CT. They propose to use a crowdbased method for ontology engineering. The current research activities further illustrate the continuous convergence of Knowledge Representation and Medical Informatics, with a focus this year on dedicated tools and methods to advance clinical care by proposing solutions to cope with the problem of semantic interoperability. Indeed, there is a need for powerful tools able to manage and interpret complex, large-scale and distributed datasets and knowledge bases, but also a need for user-friendly tools developed for the clinicians in their daily practice.
Research on Interactive Acquisition and Use of Knowledge.
1983-11-01
complex and challenging endeavor. Computer scientists faced with the problem of managing software complexity have de - veloped strict design disciplines...handle most-indeed, probably all-- phenomena in the syntax and semantics of natural language. It has also turned out to be well suited for the classes of...Semantics The previous grammar performs a de facto coordination of syntax and semantics by requiring that the (syntactically) preverbal NP play the
ERIC Educational Resources Information Center
Morales-Reyes, Alexandra; Soler, Inmaculada Gómez
2016-01-01
L2 learners' problems with English articles have been linked to learners' L1 and their access to universal semantic features (e.g., definiteness and specificity). Studies suggest that L2 adults rely on their L1 knowledge, while child L2 learners rely more on their access to semantic universals. The present study investigates whether child L2…
Image Retrieval by Color Semantics with Incomplete Knowledge.
ERIC Educational Resources Information Center
Corridoni, Jacopo M.; Del Bimbo, Alberto; Vicario, Enrico
1998-01-01
Presents a system which supports image retrieval by high-level chromatic contents, the sensations that color accordances generate on the observer. Surveys Itten's theory of color semantics and discusses image description and query specification. Presents examples of visual querying. (AEF)
A semantic model for multimodal data mining in healthcare information systems.
Iakovidis, Dimitris; Smailis, Christos
2012-01-01
Electronic health records (EHRs) are representative examples of multimodal/multisource data collections; including measurements, images and free texts. The diversity of such information sources and the increasing amounts of medical data produced by healthcare institutes annually, pose significant challenges in data mining. In this paper we present a novel semantic model that describes knowledge extracted from the lowest-level of a data mining process, where information is represented by multiple features i.e. measurements or numerical descriptors extracted from measurements, images, texts or other medical data, forming multidimensional feature spaces. Knowledge collected by manual annotation or extracted by unsupervised data mining from one or more feature spaces is modeled through generalized qualitative spatial semantics. This model enables a unified representation of knowledge across multimodal data repositories. It contributes to bridging the semantic gap, by enabling direct links between low-level features and higher-level concepts e.g. describing body parts, anatomies and pathological findings. The proposed model has been developed in web ontology language based on description logics (OWL-DL) and can be applied to a variety of data mining tasks in medical informatics. It utility is demonstrated for automatic annotation of medical data.
Learning to Read Words in a New Language Shapes the Neural Organization of the Prior Languages
Mei, Leilei; Xue, Gui; Lu, Zhong-Lin; Chen, Chuansheng; Zhang, Mingxia; He, Qinghua; Wei, Miao; Dong, Qi
2014-01-01
Learning a new language entails interactions with one's prior language(s). Much research has shown how native language affects the cognitive and neural mechanisms of a new language, but little is known about whether and how learning a new language shapes the neural mechanisms of prior language(s). In two experiments in the current study, we used an artificial language training paradigm in combination with fMRI to examine (1) the effects of different linguistic components (phonology and semantics) of a new language on the neural process of prior languages (i.e., native and second languages), and (2) whether such effects were modulated by the proficiency level in the new language. Results of Experiment 1 showed that when the training in a new language involved semantics (as opposed to only visual forms and phonology), neural activity during word reading in the native language (Chinese) was reduced in several reading-related regions, including the left pars opercularis, pars triangularis, bilateral inferior temporal gyrus, fusiform gyrus, and inferior occipital gyrus. Results of Experiment 2 replicated the results of Experiment 1 and further found that semantic training also affected neural activity during word reading in the subjects’ second language (English). Furthermore, we found that the effects of the new language were modulated by the subjects’ proficiency level in the new language. These results provide critical imaging evidence for the influence of learning to read words in a new language on word reading in native and second languages. PMID:25447375
Context-rich semantic framework for effective data-to-decisions in coalition networks
NASA Astrophysics Data System (ADS)
Grueneberg, Keith; de Mel, Geeth; Braines, Dave; Wang, Xiping; Calo, Seraphin; Pham, Tien
2013-05-01
In a coalition context, data fusion involves combining of soft (e.g., field reports, intelligence reports) and hard (e.g., acoustic, imagery) sensory data such that the resulting output is better than what it would have been if the data are taken individually. However, due to the lack of explicit semantics attached with such data, it is difficult to automatically disseminate and put the right contextual data in the hands of the decision makers. In order to understand the data, explicit meaning needs to be added by means of categorizing and/or classifying the data in relationship to each other from base reference sources. In this paper, we present a semantic framework that provides automated mechanisms to expose real-time raw data effectively by presenting appropriate information needed for a given situation so that an informed decision could be made effectively. The system utilizes controlled natural language capabilities provided by the ITA (International Technology Alliance) Controlled English (CE) toolkit to provide a human-friendly semantic representation of messages so that the messages can be directly processed in human/machine hybrid environments. The Real-time Semantic Enrichment (RTSE) service adds relevant contextual information to raw data streams from domain knowledge bases using declarative rules. The rules define how the added semantics and context information are derived and stored in a semantic knowledge base. The software framework exposes contextual information from a variety of hard and soft data sources in a fast, reliable manner so that an informed decision can be made using semantic queries in intelligent software systems.
A Formal Theory for Modular ERDF Ontologies
NASA Astrophysics Data System (ADS)
Analyti, Anastasia; Antoniou, Grigoris; Damásio, Carlos Viegas
The success of the Semantic Web is impossible without any form of modularity, encapsulation, and access control. In an earlier paper, we extended RDF graphs with weak and strong negation, as well as derivation rules. The ERDF #n-stable model semantics of the extended RDF framework (ERDF) is defined, extending RDF(S) semantics. In this paper, we propose a framework for modular ERDF ontologies, called modular ERDF framework, which enables collaborative reasoning over a set of ERDF ontologies, while support for hidden knowledge is also provided. In particular, the modular ERDF stable model semantics of modular ERDF ontologies is defined, extending the ERDF #n-stable model semantics. Our proposed framework supports local semantics and different points of view, local closed-world and open-world assumptions, and scoped negation-as-failure. Several complexity results are provided.
Interhemispheric Differences in Knowledge of Animals Among Patients With Semantic Dementia
Mendez, Mario F.; Kremen, Sarah A.; Tsai, Po-Heng; Shapira, Jill S.
2011-01-01
Objective To investigate interhemispheric differences on naming and fluency tasks for living versus nonliving things among patients with semantic dementia (SD). Background In SD, left-temporal involvement impairs language and word comprehension, and right-temporal involvement impairs facial recognition. There may be other interhemispheric differences, particularly in the animate-inanimate dichotomy. Method On the basis of magnetic resonance imaging (MRI) ratings of anterior temporal atrophy, 36 patients who met criteria for SD were divided into 21 with left-predominant and 11 with right-predominant involvement (4 others were too symmetric for analysis). The left and right-predominant groups were compared on naming, fluency, and facial recognition tests. Results Consistent with greater language impairment, the left-predominant patients had worse naming, especially inanimate and letter fluency, than the right-predominant patients. In contrast, difference in scores suggested selective impairment of animal naming, animal name fluency, and semantic knowledge for animate items among the right-predominant patients. Proportionally more right than left-predominant patients misnamed animal items and faces. Conclusions These findings support interhemispheric differences in animal knowledge. Whereas left-predominant SD equally affects animate and inanimate words from language involvement, right-predominant SD, with greater sparing of language, continues to impair other semantic aspects of animals. The right anterior temporal region seems to make a unique contribution to knowledge of living things. PMID:21042206
Knowledge Retrieval Solutions.
ERIC Educational Resources Information Center
Khan, Kamran
1998-01-01
Excalibur RetrievalWare offers true knowledge retrieval solutions. Its fundamental technologies, Adaptive Pattern Recognition Processing and Semantic Networks, have capabilities for knowledge discovery and knowledge management of full-text, structured and visual information. The software delivers a combination of accuracy, extensibility,…
LIS Professionals as Knowledge Engineers.
ERIC Educational Resources Information Center
Poulter, Alan; And Others
1994-01-01
Considers the role of library and information science professionals as knowledge engineers. Highlights include knowledge acquisition, including personal experience, interviews, protocol analysis, observation, multidimensional sorting, printed sources, and machine learning; knowledge representation, including production rules and semantic nets;…
Ontology-based knowledge representation for resolution of semantic heterogeneity in GIS
NASA Astrophysics Data System (ADS)
Liu, Ying; Xiao, Han; Wang, Limin; Han, Jialing
2017-07-01
Lack of semantic interoperability in geographical information systems has been identified as the main obstacle for data sharing and database integration. The new method should be found to overcome the problems of semantic heterogeneity. Ontologies are considered to be one approach to support geographic information sharing. This paper presents an ontology-driven integration approach to help in detecting and possibly resolving semantic conflicts. Its originality is that each data source participating in the integration process contains an ontology that defines the meaning of its own data. This approach ensures the automation of the integration through regulation of semantic integration algorithm. Finally, land classification in field GIS is described as the example.
Distributed semantic networks and CLIPS
NASA Technical Reports Server (NTRS)
Snyder, James; Rodriguez, Tony
1991-01-01
Semantic networks of frames are commonly used as a method of reasoning in many problems. In most of these applications the semantic network exists as a single entity in a single process environment. Advances in workstation hardware provide support for more sophisticated applications involving multiple processes, interacting in a distributed environment. In these applications the semantic network may well be distributed over several concurrently executing tasks. This paper describes the design and implementation of a frame based, distributed semantic network in which frames are accessed both through C Language Integrated Production System (CLIPS) expert systems and procedural C++ language programs. The application area is a knowledge based, cooperative decision making model utilizing both rule based and procedural experts.
Refining Automatically Extracted Knowledge Bases Using Crowdsourcing.
Li, Chunhua; Zhao, Pengpeng; Sheng, Victor S; Xian, Xuefeng; Wu, Jian; Cui, Zhiming
2017-01-01
Machine-constructed knowledge bases often contain noisy and inaccurate facts. There exists significant work in developing automated algorithms for knowledge base refinement. Automated approaches improve the quality of knowledge bases but are far from perfect. In this paper, we leverage crowdsourcing to improve the quality of automatically extracted knowledge bases. As human labelling is costly, an important research challenge is how we can use limited human resources to maximize the quality improvement for a knowledge base. To address this problem, we first introduce a concept of semantic constraints that can be used to detect potential errors and do inference among candidate facts. Then, based on semantic constraints, we propose rank-based and graph-based algorithms for crowdsourced knowledge refining, which judiciously select the most beneficial candidate facts to conduct crowdsourcing and prune unnecessary questions. Our experiments show that our method improves the quality of knowledge bases significantly and outperforms state-of-the-art automatic methods under a reasonable crowdsourcing cost.
The impact of semantic impairment on word stem completion in Alzheimer's disease.
Beauregard, M; Chertkow, H; Gold, D; Bergman, S
2001-01-01
Both the extent of semantic memory impairment and the level of processing attained during encoding might constitute critical factors in determining the amount of word-stem completion (WSC) priming encountered in Alzheimer's disease (AD) subjects. We investigated the impact of varying encoding level in AD and elderly normal subjects, using a set of stimuli ranked as "intact" or "degraded" in terms of each subject's semantic knowledge on probe questions. For both shallow and deep encoding conditions, overall priming in the two subject groups was equivalent. However, for the deep encoding condition, consisting of a semantic judgment task performed on each target word, the priming effect noted in AD subjects was significantly smaller for semantically degraded items than for semantically intact items. Results indicate that the degree of semantic impairment represents one important variable affecting the amount of WSC priming which results when deep encoding procedures are used at study.
Perceptually Guided Photo Retargeting.
Xia, Yingjie; Zhang, Luming; Hong, Richang; Nie, Liqiang; Yan, Yan; Shao, Ling
2016-04-22
We propose perceptually guided photo retargeting, which shrinks a photo by simulating a human's process of sequentially perceiving visually/semantically important regions in a photo. In particular, we first project the local features (graphlets in this paper) onto a semantic space, wherein visual cues such as global spatial layout and rough geometric context are exploited. Thereafter, a sparsity-constrained learning algorithm is derived to select semantically representative graphlets of a photo, and the selecting process can be interpreted by a path which simulates how a human actively perceives semantics in a photo. Furthermore, we learn the prior distribution of such active graphlet paths (AGPs) from training photos that are marked as esthetically pleasing by multiple users. The learned priors enforce the corresponding AGP of a retargeted photo to be maximally similar to those from the training photos. On top of the retargeting model, we further design an online learning scheme to incrementally update the model with new photos that are esthetically pleasing. The online update module makes the algorithm less dependent on the number and contents of the initial training data. Experimental results show that: 1) the proposed AGP is over 90% consistent with human gaze shifting path, as verified by the eye-tracking data, and 2) the retargeting algorithm outperforms its competitors significantly, as AGP is more indicative of photo esthetics than conventional saliency maps.
Richardson-Klavehn, A; Gardiner, J M
1998-05-01
Depth-of-processing effects on incidental perceptual memory tests could reflect (a) contamination by voluntary retrieval, (b) sensitivity of involuntary retrieval to prior conceptual processing, or (c) a deficit in lexical processing during graphemic study tasks that affects involuntary retrieval. The authors devised an extension of incidental test methodology--making conjunctive predictions about response times as well as response proportions--to discriminate among these alternatives. They used graphemic, phonemic, and semantic study tasks, and a word-stem completion test with incidental, intentional, and inclusion instructions. Semantic study processing was superior to phonemic study processing in the intentional and inclusion tests, but semantic and phonemic study processing produced equal priming in the incidental test, showing that priming was uncontaminated by voluntary retrieval--a conclusion reinforced by the response-time data--and that priming was insensitive to prior conceptual processing. The incidental test nevertheless showed a priming deficit following graphemic study processing, supporting the lexical-processing hypothesis. Adding a lexical decision to the 3 study tasks eliminated the priming deficit following graphemic study processing, but did not influence priming following phonemic and semantic processing. The results provide the first clear evidence that depth-of-processing effects on perceptual priming can reflect lexical processes, rather than voluntary contamination or conceptual processes.
Late positive slow waves as markers of chunking during encoding
Nogueira, Ana M. L.; Bueno, Orlando F. A.; Manzano, Gilberto M.; Kohn, André F.; Pompéia, Sabine
2015-01-01
Electrophysiological markers of chunking of words during encoding have mostly been shown in studies that present pairs of related stimuli. In these cases it is difficult to disentangle cognitive processes that reflect distinctiveness (i.e., conspicuous items because they are related), perceived association between related items and unified representations of various items, or chunking. Here, we propose a paradigm that enables the determination of a separate Event-related Potential (ERP) marker of these cognitive processes using sequentially related word triads. Twenty-three young healthy individuals viewed 80 15-word lists composed of unrelated items except for the three words in the middle serial positions (triads), which could be either unrelated (control list), related perceptually, phonetically or semantically. ERP amplitudes were measured at encoding of each one of the words in the triads. We analyzed two latency intervals (350–400 and 400–800 ms) at midline locations. Behaviorally, we observed a progressive facilitation in the immediate free recall of the words in the triads depending on the relations between their items (control < perceptual < phonetic < semantic), but only semantically related items were recalled as chunks. P300-like deflections were observed for perceptually deviant stimuli. A reduction of amplitude of a component akin to the N400 was found for words that were phonetically and semantically associated with prior items and therefore were not associated to chunking. Positive slow wave (PSW) amplitudes increased as successive phonetically and semantically related items were presented, but they were observed earlier and were more prominent at Fz for semantic associates. PSWs at Fz and Cz also correlated with recall of semantic word chunks. This confirms prior claims that PSWs at Fz are potential markers of chunking which, in the proposed paradigm, were modulated differently from the detection of deviant stimuli and of relations between stimuli. PMID:26283984
Semantic Modeling of Requirements: Leveraging Ontologies in Systems Engineering
ERIC Educational Resources Information Center
Mir, Masood Saleem
2012-01-01
The interdisciplinary nature of "Systems Engineering" (SE), having "stakeholders" from diverse domains with orthogonal facets, and need to consider all stages of "lifecycle" of system during conception, can benefit tremendously by employing "Knowledge Engineering" (KE) to achieve semantic agreement among all…
Automatic Semantic Facilitation in Anterior Temporal Cortex Revealed through Multimodal Neuroimaging
Gramfort, Alexandre; Hämäläinen, Matti S.; Kuperberg, Gina R.
2013-01-01
A core property of human semantic processing is the rapid, facilitatory influence of prior input on extracting the meaning of what comes next, even under conditions of minimal awareness. Previous work has shown a number of neurophysiological indices of this facilitation, but the mapping between time course and localization—critical for separating automatic semantic facilitation from other mechanisms—has thus far been unclear. In the current study, we used a multimodal imaging approach to isolate early, bottom-up effects of context on semantic memory, acquiring a combination of electroencephalography (EEG), magnetoencephalography (MEG), and functional magnetic resonance imaging (fMRI) measurements in the same individuals with a masked semantic priming paradigm. Across techniques, the results provide a strikingly convergent picture of early automatic semantic facilitation. Event-related potentials demonstrated early sensitivity to semantic association between 300 and 500 ms; MEG localized the differential neural response within this time window to the left anterior temporal cortex, and fMRI localized the effect more precisely to the left anterior superior temporal gyrus, a region previously implicated in semantic associative processing. However, fMRI diverged from early EEG/MEG measures in revealing semantic enhancement effects within frontal and parietal regions, perhaps reflecting downstream attempts to consciously access the semantic features of the masked prime. Together, these results provide strong evidence that automatic associative semantic facilitation is realized as reduced activity within the left anterior superior temporal cortex between 300 and 500 ms after a word is presented, and emphasize the importance of multimodal neuroimaging approaches in distinguishing the contributions of multiple regions to semantic processing. PMID:24155321
From Data to Semantic Information
NASA Astrophysics Data System (ADS)
Floridi, Luciano
2003-06-01
There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information (SDI) as meaningful data, in favour of the Dretske-Grice approach: meaningful and well-formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is incorrect because truth-values do not supervene on semantic information, and misinformation (that is, false semantic information) is not a type of semantic information, but pseudo-information, that is not semantic information at all. This is shown by arguing that none of the reasons for interpreting misinformation as a type of semantic information is convincing, whilst there are compelling reasons to treat it as pseudo-information. As a consequence, SDI is revised to include a necessary truth-condition. The last section summarises the main results of the paper and indicates the important implications of the revised definition for the analysis of the deflationary theories of truth, the standard definition of knowledge and the classic, quantitative theory of semantic information.
Knowledge-based understanding of aerial surveillance video
NASA Astrophysics Data System (ADS)
Cheng, Hui; Butler, Darren
2006-05-01
Aerial surveillance has long been used by the military to locate, monitor and track the enemy. Recently, its scope has expanded to include law enforcement activities, disaster management and commercial applications. With the ever-growing amount of aerial surveillance video acquired daily, there is an urgent need for extracting actionable intelligence in a timely manner. Furthermore, to support high-level video understanding, this analysis needs to go beyond current approaches and consider the relationships, motivations and intentions of the objects in the scene. In this paper we propose a system for interpreting aerial surveillance videos that automatically generates a succinct but meaningful description of the observed regions, objects and events. For a given video, the semantics of important regions and objects, and the relationships between them, are summarised into a semantic concept graph. From this, a textual description is derived that provides new search and indexing options for aerial video and enables the fusion of aerial video with other information modalities, such as human intelligence, reports and signal intelligence. Using a Mixture-of-Experts video segmentation algorithm an aerial video is first decomposed into regions and objects with predefined semantic meanings. The objects are then tracked and coerced into a semantic concept graph and the graph is summarized spatially, temporally and semantically using ontology guided sub-graph matching and re-writing. The system exploits domain specific knowledge and uses a reasoning engine to verify and correct the classes, identities and semantic relationships between the objects. This approach is advantageous because misclassifications lead to knowledge contradictions and hence they can be easily detected and intelligently corrected. In addition, the graph representation highlights events and anomalies that a low-level analysis would overlook.
Federmeier, Kara D.
2017-01-01
There is growing recognition that some important forms of long-term memory are difficult to classify into one of the well-studied memory subtypes. One example is personal semantics. Like the episodes that are stored as part of one’s autobiography, personal semantics is linked to an individual, yet, like general semantic memory, it is detached from a specific encoding context. Access to general semantics elicits an electrophysiological response known as the N400, which has been characterized across three decades of research; surprisingly, this response has not been fully examined in the context of personal semantics. In this study, we assessed responses to congruent and incongruent statements about people’s own, personal preferences. We found that access to personal preferences elicited N400 responses, with congruency effects that were similar in latency and distribution to those for general semantic statements elicited from the same participants. These results suggest that the processing of personal and general semantics share important functional and neurobiological features. PMID:26825011
Context-Aware Adaptive Hybrid Semantic Relatedness in Biomedical Science
NASA Astrophysics Data System (ADS)
Emadzadeh, Ehsan
Text mining of biomedical literature and clinical notes is a very active field of research in biomedical science. Semantic analysis is one of the core modules for different Natural Language Processing (NLP) solutions. Methods for calculating semantic relatedness of two concepts can be very useful in solutions solving different problems such as relationship extraction, ontology creation and question / answering [1--6]. Several techniques exist in calculating semantic relatedness of two concepts. These techniques utilize different knowledge sources and corpora. So far, researchers attempted to find the best hybrid method for each domain by combining semantic relatedness techniques and data sources manually. In this work, attempts were made to eliminate the needs for manually combining semantic relatedness methods targeting any new contexts or resources through proposing an automated method, which attempted to find the best combination of semantic relatedness techniques and resources to achieve the best semantic relatedness score in every context. This may help the research community find the best hybrid method for each context considering the available algorithms and resources.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yue, Peng; Gong, Jianya; Di, Liping
Abstract A geospatial catalogue service provides a network-based meta-information repository and interface for advertising and discovering shared geospatial data and services. Descriptive information (i.e., metadata) for geospatial data and services is structured and organized in catalogue services. The approaches currently available for searching and using that information are often inadequate. Semantic Web technologies show promise for better discovery methods by exploiting the underlying semantics. Such development needs special attention from the Cyberinfrastructure perspective, so that the traditional focus on discovery of and access to geospatial data can be expanded to support the increased demand for processing of geospatial information andmore » discovery of knowledge. Semantic descriptions for geospatial data, services, and geoprocessing service chains are structured, organized, and registered through extending elements in the ebXML Registry Information Model (ebRIM) of a geospatial catalogue service, which follows the interface specifications of the Open Geospatial Consortium (OGC) Catalogue Services for the Web (CSW). The process models for geoprocessing service chains, as a type of geospatial knowledge, are captured, registered, and discoverable. Semantics-enhanced discovery for geospatial data, services/service chains, and process models is described. Semantic search middleware that can support virtual data product materialization is developed for the geospatial catalogue service. The creation of such a semantics-enhanced geospatial catalogue service is important in meeting the demands for geospatial information discovery and analysis in Cyberinfrastructure.« less
ERIC Educational Resources Information Center
Whitney, Carin; Kirk, Marie; O'Sullivan, Jamie; Ralph, Matthew A. Lambon; Jefferies, Elizabeth
2012-01-01
To understand the meanings of words and objects, we need to have knowledge about these items themselves plus executive mechanisms that compute and manipulate semantic information in a task-appropriate way. The neural basis for semantic control remains controversial. Neuroimaging studies have focused on the role of the left inferior frontal gyrus…
KOJAK: Scalable Semantic Link Discovery Via Integrated Knowledge-Based and Statistical Reasoning
2006-11-01
program can find interesting connections in a network without having to learn the patterns of interestingness beforehand. The key advantage of our...Interesting Instances in Semantic Graphs Below we describe how the UNICORN framework can discover interesting instances in a multi-relational dataset...We can now describe how UNICORN solves the first problem of finding the top interesting nodes in a semantic net by ranking them according to
Learning semantic and visual similarity for endomicroscopy video retrieval.
Andre, Barbara; Vercauteren, Tom; Buchner, Anna M; Wallace, Michael B; Ayache, Nicholas
2012-06-01
Content-based image retrieval (CBIR) is a valuable computer vision technique which is increasingly being applied in the medical community for diagnosis support. However, traditional CBIR systems only deliver visual outputs, i.e., images having a similar appearance to the query, which is not directly interpretable by the physicians. Our objective is to provide a system for endomicroscopy video retrieval which delivers both visual and semantic outputs that are consistent with each other. In a previous study, we developed an adapted bag-of-visual-words method for endomicroscopy retrieval, called "Dense-Sift," that computes a visual signature for each video. In this paper, we present a novel approach to complement visual similarity learning with semantic knowledge extraction, in the field of in vivo endomicroscopy. We first leverage a semantic ground truth based on eight binary concepts, in order to transform these visual signatures into semantic signatures that reflect how much the presence of each semantic concept is expressed by the visual words describing the videos. Using cross-validation, we demonstrate that, in terms of semantic detection, our intuitive Fisher-based method transforming visual-word histograms into semantic estimations outperforms support vector machine (SVM) methods with statistical significance. In a second step, we propose to improve retrieval relevance by learning an adjusted similarity distance from a perceived similarity ground truth. As a result, our distance learning method allows to statistically improve the correlation with the perceived similarity. We also demonstrate that, in terms of perceived similarity, the recall performance of the semantic signatures is close to that of visual signatures and significantly better than those of several state-of-the-art CBIR methods. The semantic signatures are thus able to communicate high-level medical knowledge while being consistent with the low-level visual signatures and much shorter than them. In our resulting retrieval system, we decide to use visual signatures for perceived similarity learning and retrieval, and semantic signatures for the output of an additional information, expressed in the endoscopist own language, which provides a relevant semantic translation of the visual retrieval outputs.
Spatt, Josef; Bak, Thomas; Bozeat, Sasha; Patterson, Karalyn; Hodges, John R
2002-05-01
To investigate the nature of the apraxia in corticobasal degeneration (CBD) five patients with CBD and five matched controls were compared on tests of: i) meaningless and symbolic gesture production, ii) a battery of semantic tasks based on 20 everyday items (involving naming and picture-picture matching according to semantic attributes, matching gestures-to-objects, object usage from name and with the real object) and iii) a novel tool test of mechanical problem solving. All five patients showed severe impairment in the production of meaningless and symbolic gestures from command, and by imitation, and were also impaired when using real objects. Deficits were not, however, restricted to action production: four were unable to match gestures to objects and all five showed impairment in the selection and usage of novel tools in the mechanical problem solving task. Surprising was the finding of an additional semantic knowledge breakdown in three cases, two of whom were markedly anomic. The apraxia in CBD is, therefore, multifactorial. There is profound breakdown in the organisation and co-ordination of motor programming. In addition, patients show central deficits in action knowledge and mechanical problem solving, which has been linked to parietal lobe pathology. General semantic memory may also be affected in CBD in some cases and this may then contribute to impaired object usage. This combination of more than one deficit relevant for object use may explain why CBD patients are far more disabled by their dyspraxia in everyday life than any other patient group.
Zhang, Yi-Fan; Tian, Yu; Zhou, Tian-Shu; Araki, Kenji; Li, Jing-Song
2016-01-01
The broad adoption of clinical decision support systems within clinical practice has been hampered mainly by the difficulty in expressing domain knowledge and patient data in a unified formalism. This paper presents a semantic-based approach to the unified representation of healthcare domain knowledge and patient data for practical clinical decision making applications. A four-phase knowledge engineering cycle is implemented to develop a semantic healthcare knowledge base based on an HL7 reference information model, including an ontology to model domain knowledge and patient data and an expression repository to encode clinical decision making rules and queries. A semantic clinical decision support system is designed to provide patient-specific healthcare recommendations based on the knowledge base and patient data. The proposed solution is evaluated in the case study of type 2 diabetes mellitus inpatient management. The knowledge base is successfully instantiated with relevant domain knowledge and testing patient data. Ontology-level evaluation confirms model validity. Application-level evaluation of diagnostic accuracy reaches a sensitivity of 97.5%, a specificity of 100%, and a precision of 98%; an acceptance rate of 97.3% is given by domain experts for the recommended care plan orders. The proposed solution has been successfully validated in the case study as providing clinical decision support at a high accuracy and acceptance rate. The evaluation results demonstrate the technical feasibility and application prospect of our approach. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
JournalMap: Geo-semantic searching for relevant knowledge
USDA-ARS?s Scientific Manuscript database
Ecologists struggling to understand rapidly changing environments and evolving ecosystem threats need quick access to relevant research and documentation of natural systems. The advent of semantic and aggregation searching (e.g., Google Scholar, Web of Science) has made it easier to find useful lite...
Constructive Ontology Engineering
ERIC Educational Resources Information Center
Sousan, William L.
2010-01-01
The proliferation of the Semantic Web depends on ontologies for knowledge sharing, semantic annotation, data fusion, and descriptions of data for machine interpretation. However, ontologies are difficult to create and maintain. In addition, their structure and content may vary depending on the application and domain. Several methods described in…
Interoperability in Personalized Adaptive Learning
ERIC Educational Resources Information Center
Aroyo, Lora; Dolog, Peter; Houben, Geert-Jan; Kravcik, Milos; Naeve, Ambjorn; Nilsson, Mikael; Wild, Fridolin
2006-01-01
Personalized adaptive learning requires semantic-based and context-aware systems to manage the Web knowledge efficiently as well as to achieve semantic interoperability between heterogeneous information resources and services. The technological and conceptual differences can be bridged either by means of standards or via approaches based on the…
Semantic based man-machine interface for real-time communication
NASA Technical Reports Server (NTRS)
Ali, M.; Ai, C.-S.
1988-01-01
A flight expert system (FLES) was developed to assist pilots in monitoring, diagnosing and recovering from in-flight faults. To provide a communications interface between the flight crew and FLES, a natural language interface (NALI) was implemented. Input to NALI is processed by three processors: (1) the semantics parser; (2) the knowledge retriever; and (3) the response generator. First the semantic parser extracts meaningful words and phrases to generate an internal representation of the query. At this point, the semantic parser has the ability to map different input forms related to the same concept into the same internal representation. Then the knowledge retriever analyzes and stores the context of the query to aid in resolving ellipses and pronoun references. At the end of this process, a sequence of retrievel functions is created as a first step in generating the proper response. Finally, the response generator generates the natural language response to the query. The architecture of NALI was designed to process both temporal and nontemporal queries. The architecture and implementation of NALI are described.
A memory learning framework for effective image retrieval.
Han, Junwei; Ngan, King N; Li, Mingjing; Zhang, Hong-Jiang
2005-04-01
Most current content-based image retrieval systems are still incapable of providing users with their desired results. The major difficulty lies in the gap between low-level image features and high-level image semantics. To address the problem, this study reports a framework for effective image retrieval by employing a novel idea of memory learning. It forms a knowledge memory model to store the semantic information by simply accumulating user-provided interactions. A learning strategy is then applied to predict the semantic relationships among images according to the memorized knowledge. Image queries are finally performed based on a seamless combination of low-level features and learned semantics. One important advantage of our framework is its ability to efficiently annotate images and also propagate the keyword annotation from the labeled images to unlabeled images. The presented algorithm has been integrated into a practical image retrieval system. Experiments on a collection of 10,000 general-purpose images demonstrate the effectiveness of the proposed framework.
Zannino, Gian Daniele; Perri, Roberta; Monaco, Marco; Caltagirone, Carlo; Luzzi, Simona; Carlesimo, Giovanni A
2014-01-01
According to the semantic hub hypothesis, a supramodal semantic hub is equally needed to deal with verbal and extraverbal "surface" representations. Damage to the supramodal hub is thought to underlie the crossmodal impairment observed in selective semantic deficits. In the present paper, we provide evidence supporting an alternative view: we hold that semantic impairment is not equal across domains but affects verbal behavior disproportionately. We investigated our hypothesis by manipulating the verbal load in an object decision task. Two pathological groups showing different levels of semantic impairment were enrolled together with their normal controls. The severe group included 10 subjects with semantic dementia and the mild group 10 subjects with Alzheimer's disease. In keeping with our hypothesis, when shifting from the low verbal load to the high verbal load condition, brain-damaged individuals, as compared to controls, showed a disproportionate impairment as a function of the severity of their semantic deficit. Copyright © 2013 Elsevier Inc. All rights reserved.
Biomedical semantics in the Semantic Web
2011-01-01
The Semantic Web offers an ideal platform for representing and linking biomedical information, which is a prerequisite for the development and application of analytical tools to address problems in data-intensive areas such as systems biology and translational medicine. As for any new paradigm, the adoption of the Semantic Web offers opportunities and poses questions and challenges to the life sciences scientific community: which technologies in the Semantic Web stack will be more beneficial for the life sciences? Is biomedical information too complex to benefit from simple interlinked representations? What are the implications of adopting a new paradigm for knowledge representation? What are the incentives for the adoption of the Semantic Web, and who are the facilitators? Is there going to be a Semantic Web revolution in the life sciences? We report here a few reflections on these questions, following discussions at the SWAT4LS (Semantic Web Applications and Tools for Life Sciences) workshop series, of which this Journal of Biomedical Semantics special issue presents selected papers from the 2009 edition, held in Amsterdam on November 20th. PMID:21388570
Biomedical semantics in the Semantic Web.
Splendiani, Andrea; Burger, Albert; Paschke, Adrian; Romano, Paolo; Marshall, M Scott
2011-03-07
The Semantic Web offers an ideal platform for representing and linking biomedical information, which is a prerequisite for the development and application of analytical tools to address problems in data-intensive areas such as systems biology and translational medicine. As for any new paradigm, the adoption of the Semantic Web offers opportunities and poses questions and challenges to the life sciences scientific community: which technologies in the Semantic Web stack will be more beneficial for the life sciences? Is biomedical information too complex to benefit from simple interlinked representations? What are the implications of adopting a new paradigm for knowledge representation? What are the incentives for the adoption of the Semantic Web, and who are the facilitators? Is there going to be a Semantic Web revolution in the life sciences?We report here a few reflections on these questions, following discussions at the SWAT4LS (Semantic Web Applications and Tools for Life Sciences) workshop series, of which this Journal of Biomedical Semantics special issue presents selected papers from the 2009 edition, held in Amsterdam on November 20th.
Shi, Longxiang; Li, Shijian; Yang, Xiaoran; Qi, Jiaheng; Pan, Gang; Zhou, Binbin
2017-01-01
With the explosion of healthcare information, there has been a tremendous amount of heterogeneous textual medical knowledge (TMK), which plays an essential role in healthcare information systems. Existing works for integrating and utilizing the TMK mainly focus on straightforward connections establishment and pay less attention to make computers interpret and retrieve knowledge correctly and quickly. In this paper, we explore a novel model to organize and integrate the TMK into conceptual graphs. We then employ a framework to automatically retrieve knowledge in knowledge graphs with a high precision. In order to perform reasonable inference on knowledge graphs, we propose a contextual inference pruning algorithm to achieve efficient chain inference. Our algorithm achieves a better inference result with precision and recall of 92% and 96%, respectively, which can avoid most of the meaningless inferences. In addition, we implement two prototypes and provide services, and the results show our approach is practical and effective.
Yang, Xiaoran; Qi, Jiaheng; Pan, Gang; Zhou, Binbin
2017-01-01
With the explosion of healthcare information, there has been a tremendous amount of heterogeneous textual medical knowledge (TMK), which plays an essential role in healthcare information systems. Existing works for integrating and utilizing the TMK mainly focus on straightforward connections establishment and pay less attention to make computers interpret and retrieve knowledge correctly and quickly. In this paper, we explore a novel model to organize and integrate the TMK into conceptual graphs. We then employ a framework to automatically retrieve knowledge in knowledge graphs with a high precision. In order to perform reasonable inference on knowledge graphs, we propose a contextual inference pruning algorithm to achieve efficient chain inference. Our algorithm achieves a better inference result with precision and recall of 92% and 96%, respectively, which can avoid most of the meaningless inferences. In addition, we implement two prototypes and provide services, and the results show our approach is practical and effective. PMID:28299322
Enhancing Users' Participation in Business Process Modeling through Ontology-Based Training
NASA Astrophysics Data System (ADS)
Macris, A.; Malamateniou, F.; Vassilacopoulos, G.
Successful business process design requires active participation of users who are familiar with organizational activities and business process modelling concepts. Hence, there is a need to provide users with reusable, flexible, agile and adaptable training material in order to enable them instil their knowledge and expertise in business process design and automation activities. Knowledge reusability is of paramount importance in designing training material on process modelling since it enables users participate actively in process design/redesign activities stimulated by the changing business environment. This paper presents a prototype approach for the design and use of training material that provides significant advantages to both the designer (knowledge - content reusability and semantic web enabling) and the user (semantic search, knowledge navigation and knowledge dissemination). The approach is based on externalizing domain knowledge in the form of ontology-based knowledge networks (i.e. training scenarios serving specific training needs) so that it is made reusable.
Smith, Mary Lou; Lah, Suncica
2011-09-01
This study explored verbal semantic and episodic memory in children with unilateral temporal lobe epilepsy to determine whether they had impairments in both or only 1 aspect of memory, and to examine relations between performance in the 2 domains. Sixty-six children and adolescents (37 with seizures of left temporal lobe onset, 29 with right-sided onset) were given 4 tasks assessing different aspects of semantic memory (picture naming, fluency, knowledge of facts, knowledge of word meanings) and 2 episodic memory tasks (story recall, word list recall). High rates of impairments were observed across tasks, and no differences were found related to the laterality of the seizures. Individual patient analyses showed that there was a double dissociation between the 2 aspects of memory in that some children were impaired on episodic but not semantic memory, whereas others showed intact episodic but impaired semantic memory. This double dissociation suggests that these 2 memory systems may develop independently in the context of temporal lobe pathology, perhaps related to differential effects of dysfunction in the lateral and mesial temporal lobe structures. PsycINFO Database Record (c) 2011 APA, all rights reserved.
Knowledge Provenance in Semantic Wikis
NASA Astrophysics Data System (ADS)
Ding, L.; Bao, J.; McGuinness, D. L.
2008-12-01
Collaborative online environments with a technical Wiki infrastructure are becoming more widespread. One of the strengths of a Wiki environment is that it is relatively easy for numerous users to contribute original content and modify existing content (potentially originally generated by others). As more users begin to depend on informational content that is evolving by Wiki communities, it becomes more important to track the provenance of the information. Semantic Wikis expand upon traditional Wiki environments by adding some computationally understandable encodings of some of the terms and relationships in Wikis. We have developed a semantic Wiki environment that expands a semantic Wiki with provenance markup. Provenance of original contributions as well as modifications is encoded using the provenance markup component of the Proof Markup Language. The Wiki environment provides the provenance markup automatically, thus users are not required to make specific encodings of author, contribution date, and modification trail. Further, our Wiki environment includes a search component that understands the provenance primitives and thus can be used to provide a provenance-aware search facility. We will describe the knowledge provenance infrastructure of our Semantic Wiki and show how it is being used as the foundation of our group web site as well as a number of project web sites.
The Role of Semantic Clustering in Optimal Memory Foraging.
Montez, Priscilla; Thompson, Graham; Kello, Christopher T
2015-11-01
Recent studies of semantic memory have investigated two theories of optimal search adopted from the animal foraging literature: Lévy flights and marginal value theorem. Each theory makes different simplifying assumptions and addresses different findings in search behaviors. In this study, an experiment is conducted to test whether clustering in semantic memory may play a role in evidence for both theories. Labeled magnets and a whiteboard were used to elicit spatial representations of semantic knowledge about animals. Category recall sequences from a separate experiment were used to trace search paths over the spatial representations of animal knowledge. Results showed that spatial distances between animal names arranged on the whiteboard were correlated with inter-response intervals (IRIs) during category recall, and distributions of both dependent measures approximated inverse power laws associated with Lévy flights. In addition, IRIs were relatively shorter when paths first entered animal clusters, and longer when they exited clusters, which is consistent with marginal value theorem. In conclusion, area-restricted searches over clustered semantic spaces may account for two different patterns of results interpreted as supporting two different theories of optimal memory foraging. Copyright © 2015 Cognitive Science Society, Inc.
Dew, Ilana T. Z.; Ritchey, Maureen; LaBar, Kevin S.; Cabeza, Roberto
2014-01-01
A fundamental idea in memory research is that items are more likely to be remembered if encoded with a semantic, rather than perceptual, processing strategy. Interestingly, this effect has been shown to reverse for emotionally arousing materials, such that perceptual processing enhances memory for emotional information or events. The current fMRI study investigated the neural mechanisms of this effect by testing how neural activations during emotional memory retrieval are influenced by the prior encoding strategy. Participants incidentally encoded emotional and neutral pictures under instructions to attend to either semantic or perceptual properties of each picture. Recognition memory was tested two days later. fMRI analyses yielded three main findings. First, right amygdalar activity associated with emotional memory strength was enhanced by prior perceptual processing. Second, prior perceptual processing of emotional pictures produced a stronger effect on recollection- than familiarity-related activations in the right amygdala and left hippocampus. Finally, prior perceptual processing enhanced amygdalar connectivity with regions strongly associated with retrieval success, including hippocampal/parahippocampal regions, visual cortex, and ventral parietal cortex. Taken together, the results specify how encoding orientations yield alterations in brain systems that retrieve emotional memories. PMID:24380867
On a categorial aspect of knowledge representation
NASA Astrophysics Data System (ADS)
Tataj, Emanuel; Mulawka, Jan; Nieznański, Edward
Adequate representation of data is crucial for modeling any type of data. To faithfully present and describe the relevant section of the world it is necessary to select the method that can easily be implemented on a computer system which will help in further description allowing reasoning. The main objective of this contribution is to present methods of knowledge representation using categorial approach. Next to identify the main advantages for computer implementation. Categorical aspect of knowledge representation is considered in semantic networks realisation. Such method borrows already known metaphysics properties for data modeling process. The potential topics of further development of categorical semantic networks implementations are also underlined.
Brunetti, Enzo; Maldonado, Pedro E; Aboitiz, Francisco
2013-01-01
During monitoring of the discourse, the detection of the relevance of incoming lexical information could be critical for its incorporation to update mental representations in memory. Because, in these situations, the relevance for lexical information is defined by abstract rules that are maintained in memory, a central aspect to elucidate is how an abstract level of knowledge maintained in mind mediates the detection of the lower-level semantic information. In the present study, we propose that neuronal oscillations participate in the detection of relevant lexical information, based on "kept in mind" rules deriving from more abstract semantic information. We tested our hypothesis using an experimental paradigm that restricted the detection of relevance to inferences based on explicit information, thus controlling for ambiguities derived from implicit aspects. We used a categorization task, in which the semantic relevance was previously defined based on the congruency between a kept in mind category (abstract knowledge), and the lexical semantic information presented. Our results show that during the detection of the relevant lexical information, phase synchronization of neuronal oscillations selectively increases in delta and theta frequency bands during the interval of semantic analysis. These increments occurred irrespective of the semantic category maintained in memory, had a temporal profile specific for each subject, and were mainly induced, as they had no effect on the evoked mean global field power. Also, recruitment of an increased number of pairs of electrodes was a robust observation during the detection of semantic contingent words. These results are consistent with the notion that the detection of relevant lexical information based on a particular semantic rule, could be mediated by increasing the global phase synchronization of neuronal oscillations, which may contribute to the recruitment of an extended number of cortical regions.
Reilly, Jamie; Peelle, Jonathan E; Garcia, Amanda; Crutch, Sebastian J
2016-01-01
Biological plausibility is an essential constraint for any viable model of semantic memory. Yet, we have only the most rudimentary understanding of how the human brain conducts abstract symbolic transformations that underlie word and object meaning. Neuroscience has evolved a sophisticated arsenal of techniques for elucidating the architecture of conceptual representation. Nevertheless, theoretical convergence remains elusive. Here we describe several contrastive approaches to the organization of semantic knowledge, and in turn we offer our own perspective on two recurring questions in semantic memory research: 1) to what extent are conceptual representations mediated by sensorimotor knowledge (i.e., to what degree is semantic memory embodied)? 2) How might an embodied semantic system represent abstract concepts such as modularity, symbol, or proposition? To address these questions, we review the merits of sensorimotor (i.e., embodied) and amodal (i.e., disembodied) semantic theories and address the neurobiological constraints underlying each. We conclude that the shortcomings of both perspectives in their extreme forms necessitate a hybrid middle ground. We accordingly propose the Dynamic Multilevel Reactivation Framework, an integrative model premised upon flexible interplay between sensorimotor and amodal symbolic representations mediated by multiple cortical hubs. We discuss applications of the Dynamic Multilevel Reactivation Framework to abstract and concrete concept representation and describe how a multidimensional conceptual topography based on emotion, sensation, and magnitude can successfully frame a semantic space containing meanings for both abstract and concrete words. The consideration of ‘abstract conceptual features’ does not diminish the role of logical and/or executive processing in activating, manipulating and using information stored in conceptual representations. Rather, it proposes that the material on which these processes operate necessarily combine pure sensorimotor information and higher-order cognitive dimensions involved in symbolic representation. PMID:27294419
Simoes Loureiro, Isabelle; Lefebvre, Laurent
2016-10-01
Taxonomic and thematic relationships are core elements of lexico-semantic networks. However, the weight of both links differs in semantic memory, with distinct support for natural and manufactured objects: natural objects tend to be more taxonomically identified while manufactured objects benefit more from the underlying thematic relationships. Alzheimer's disease (AD) causes early semantic memory impairment characterized by a category-specific deterioration, where natural objects are more sensitive to the disease than manufactured objects. However, relatively few studies have examined the progressive deterioration of specific thematic versus taxonomic relations in both categories of objects in AD. To better understand semantic memory disorganization in AD and analyze the potential interaction effect between the category (natural/manufactured), the condition (thematic/taxonomic) and AD, we will investigate the lexico-semantic network in 82 AD patients (divided into three groups depending on their global cognitive deterioration and their performance in a preliminary semantic knowledge questionnaire (mild (AD1), moderate (AD2) and advanced (AD3) stages of semantic knowledge alteration). The experimental protocol contains two tasks: an implicit semantic priming paradigm and an explicit card-sorting test that uses the same items, equally divided between natural and manufactured objects. Results show a distinct taxonomic and thematic evolution pattern with early taxonomic deterioration. Natural objects are also more vulnerable to the disease. Lastly, there is an interaction effect between the category and the condition in the priming task indicating that natural objects are more taxonomically organized and manufactured objects benefit more from both thematic and taxonomic organizations, reinforcing the idea of the robustness of this category. The theoretical accounts of these observations will be discussed in detail. Copyright © 2016 Elsevier Ltd. All rights reserved.
Reilly, Jamie; Peelle, Jonathan E; Garcia, Amanda; Crutch, Sebastian J
2016-08-01
Biological plausibility is an essential constraint for any viable model of semantic memory. Yet, we have only the most rudimentary understanding of how the human brain conducts abstract symbolic transformations that underlie word and object meaning. Neuroscience has evolved a sophisticated arsenal of techniques for elucidating the architecture of conceptual representation. Nevertheless, theoretical convergence remains elusive. Here we describe several contrastive approaches to the organization of semantic knowledge, and in turn we offer our own perspective on two recurring questions in semantic memory research: (1) to what extent are conceptual representations mediated by sensorimotor knowledge (i.e., to what degree is semantic memory embodied)? (2) How might an embodied semantic system represent abstract concepts such as modularity, symbol, or proposition? To address these questions, we review the merits of sensorimotor (i.e., embodied) and amodal (i.e., disembodied) semantic theories and address the neurobiological constraints underlying each. We conclude that the shortcomings of both perspectives in their extreme forms necessitate a hybrid middle ground. We accordingly propose the Dynamic Multilevel Reactivation Framework-an integrative model predicated upon flexible interplay between sensorimotor and amodal symbolic representations mediated by multiple cortical hubs. We discuss applications of the dynamic multilevel reactivation framework to abstract and concrete concept representation and describe how a multidimensional conceptual topography based on emotion, sensation, and magnitude can successfully frame a semantic space containing meanings for both abstract and concrete words. The consideration of 'abstract conceptual features' does not diminish the role of logical and/or executive processing in activating, manipulating and using information stored in conceptual representations. Rather, it proposes that the materials upon which these processes operate necessarily combine pure sensorimotor information and higher-order cognitive dimensions involved in symbolic representation.
Discovering Semantic Patterns in Bibliographically Coupled Documents.
ERIC Educational Resources Information Center
Qin, Jian
1999-01-01
An example of semantic pattern analysis, based on keywords selected from documents grouped by bibliographical coupling, is used to demonstrate the methodological aspects of knowledge discovery in bibliographic databases. Frequency distribution patterns suggest the existence of a common intellectual base with a wide range of specialties and…
Semantic interoperability--HL7 Version 3 compared to advanced architecture standards.
Blobel, B G M E; Engel, K; Pharow, P
2006-01-01
To meet the challenge for high quality and efficient care, highly specialized and distributed healthcare establishments have to communicate and co-operate in a semantically interoperable way. Information and communication technology must be open, flexible, scalable, knowledge-based and service-oriented as well as secure and safe. For enabling semantic interoperability, a unified process for defining and implementing the architecture, i.e. structure and functions of the cooperating systems' components, as well as the approach for knowledge representation, i.e. the used information and its interpretation, algorithms, etc. have to be defined in a harmonized way. Deploying the Generic Component Model, systems and their components, underlying concepts and applied constraints must be formally modeled, strictly separating platform-independent from platform-specific models. As HL7 Version 3 claims to represent the most successful standard for semantic interoperability, HL7 has been analyzed regarding the requirements for model-driven, service-oriented design of semantic interoperable information systems, thereby moving from a communication to an architecture paradigm. The approach is compared with advanced architectural approaches for information systems such as OMG's CORBA 3 or EHR systems such as GEHR/openEHR and CEN EN 13606 Electronic Health Record Communication. HL7 Version 3 is maturing towards an architectural approach for semantic interoperability. Despite current differences, there is a close collaboration between the teams involved guaranteeing a convergence between competing approaches.
Web service discovery among large service pools utilising semantic similarity and clustering
NASA Astrophysics Data System (ADS)
Chen, Fuzan; Li, Minqiang; Wu, Harris; Xie, Lingli
2017-03-01
With the rapid development of electronic business, Web services have attracted much attention in recent years. Enterprises can combine individual Web services to provide new value-added services. An emerging challenge is the timely discovery of close matches to service requests among large service pools. In this study, we first define a new semantic similarity measure combining functional similarity and process similarity. We then present a service discovery mechanism that utilises the new semantic similarity measure for service matching. All the published Web services are pre-grouped into functional clusters prior to the matching process. For a user's service request, the discovery mechanism first identifies matching services clusters and then identifies the best matching Web services within these matching clusters. Experimental results show that the proposed semantic discovery mechanism performs better than a conventional lexical similarity-based mechanism.
The sound of enemies and friends in the neighborhood.
Pecher, Diane; Boot, Inge; van Dantzig, Saskia; Madden, Carol J; Huber, David E; Zeelenberg, René
2011-01-01
Previous studies (e.g., Pecher, Zeelenberg, & Wagenmakers, 2005) found that semantic classification performance is better for target words with orthographic neighbors that are mostly from the same semantic class (e.g., living) compared to target words with orthographic neighbors that are mostly from the opposite semantic class (e.g., nonliving). In the present study we investigated the contribution of phonology to orthographic neighborhood effects by comparing effects of phonologically congruent orthographic neighbors (book-hook) to phonologically incongruent orthographic neighbors (sand-wand). The prior presentation of a semantically congruent word produced larger effects on subsequent animacy decisions when the previously presented word was a phonologically congruent neighbor than when it was a phonologically incongruent neighbor. In a second experiment, performance differences between target words with versus without semantically congruent orthographic neighbors were larger if the orthographic neighbors were also phonologically congruent. These results support models of visual word recognition that assume an important role for phonology in cascaded access to meaning.
Perea, M; Gotor, A
1997-02-01
Prior research has found significant associative/semantic priming effects at very short stimulus-onset asynchronies (SOAs) in experimental tasks such as lexical decision, but not in naming tasks (however, see Lukatela and Turvey, 1994). In this paper, the time course of associative priming effects was analyzed a several very short SOAs (33, 50, and 67 ms), using the masked priming paradigm (Forster and Davis, 1984), both in lexical decision (Experiment 1) and naming (Experiment 2). The results show small--but significant--associative priming effects in both tasks. Additionally, using the masked priming procedure at the 67 ms SOA. Experiments 3 and 4, shows facilitatory priming effects for both associatively and semantically (unassociated) related pairs in lexical decision and naming tasks. That is, automatic priming can be semantic. Taken together our data appear to support interactive models of word recognition in which semantic activation may influence the early stages of word processing.
Ishibashi, Ryo; Mima, Tatsuya; Fukuyama, Hidenao; Pobric, Gorana
2017-01-01
Using a variety of tools is a common and essential component of modern human life. Patients with brain damage or neurological disorders frequently have cognitive deficits in their recognition and manipulation of tools. In this study, we focused on improving tool-related cognition using transcranial direct current stimulation (tDCS). Converging evidence from neuropsychology, neuroimaging and non- invasive brain stimulation has identified the anterior temporal lobe (ATL) and inferior parietal lobule (IPL) as brain regions supporting action semantics. We observed enhanced performance in tool cognition with anodal tDCS over ATL and IPL in two cognitive tasks that require rapid access to semantic knowledge about the function or manipulation of common tools. ATL stimulation improved access to both function and manipulation knowledge of tools. The effect of IPL stimulation showed a trend toward better manipulation judgments. Our findings support previous studies of tool semantics and provide a novel approach for manipulation of underlying circuits.
Semantator: semantic annotator for converting biomedical text to linked data.
Tao, Cui; Song, Dezhao; Sharma, Deepak; Chute, Christopher G
2013-10-01
More than 80% of biomedical data is embedded in plain text. The unstructured nature of these text-based documents makes it challenging to easily browse and query the data of interest in them. One approach to facilitate browsing and querying biomedical text is to convert the plain text to a linked web of data, i.e., converting data originally in free text to structured formats with defined meta-level semantics. In this paper, we introduce Semantator (Semantic Annotator), a semantic-web-based environment for annotating data of interest in biomedical documents, browsing and querying the annotated data, and interactively refining annotation results if needed. Through Semantator, information of interest can be either annotated manually or semi-automatically using plug-in information extraction tools. The annotated results will be stored in RDF and can be queried using the SPARQL query language. In addition, semantic reasoners can be directly applied to the annotated data for consistency checking and knowledge inference. Semantator has been released online and was used by the biomedical ontology community who provided positive feedbacks. Our evaluation results indicated that (1) Semantator can perform the annotation functionalities as designed; (2) Semantator can be adopted in real applications in clinical and transactional research; and (3) the annotated results using Semantator can be easily used in Semantic-web-based reasoning tools for further inference. Copyright © 2013 Elsevier Inc. All rights reserved.
A specific cognitive deficit within semantic cognition across a multi-generational family
Briscoe, Josie; Chilvers, Rebecca; Baldeweg, Torsten; Skuse, David
2012-01-01
We report a study of eight members of a single family (aged 8–72 years), who all show a specific deficit in linking semantic knowledge to language. All affected members of the family had high levels of overall intelligence; however, they had profound difficulties in prose and sentence recall, listening comprehension and naming. The behavioural deficit was remarkably consistent across affected family members. Structural neuroimaging data revealed grey matter abnormalities in the left infero-temporal cortex and fusiform gyri: brain areas that have been associated with integrative semantics. This family demonstrates, to our knowledge, the first example of a heritable, highly specific abnormality affecting the interface between language and cognition in humans and has important implications for our understanding of the genetic basis of cognition. PMID:22719041
Fellner, Marie-Christin; Bäuml, Karl-Heinz T; Hanslmayr, Simon
2013-10-01
Memory crucially depends on the way information is processed during encoding. Differences in processes during encoding not only lead to differences in memory performance but also rely on different brain networks. Although these assumptions are corroborated by several previous fMRI and ERP studies, little is known about how brain oscillations dissociate between different memory encoding tasks. The present study therefore compared encoding related brain oscillatory activity elicited by two very efficient encoding tasks: a typical deep semantic item feature judgment task and a more elaborative survival encoding task. Subjects were asked to judge words either for survival relevance or for animacy, as indicated by a cue presented prior to the item. This allowed dissociating pre-item activity from item-related activity for both tasks. Replicating prior studies, survival processing led to higher recognition performance than semantic processing. Successful encoding in the semantic condition was reflected by a strong decrease in alpha and beta power, whereas successful encoding in the survival condition was related to increased alpha and beta long-range phase synchrony. Moreover, a pre-item subsequent memory effect in theta power was found which did not vary with encoding condition. These results show that measures of local synchrony (power) and global long range-synchrony (phase synchronization) dissociate between memory encoding processes. Whereas semantic encoding was reflected in decreases in local synchrony, increases in global long range synchrony were related to elaborative survival encoding, presumably reflecting the involvement of a more widespread cortical network in this task. Copyright © 2013 Elsevier Inc. All rights reserved.
Allen, Mark D; Owens, Tyler E
2008-07-01
Allen [Allen, M. D. (2005). The preservation of verb subcategory knowledge in a spoken language comprehension deficit. Brain and Language, 95, 255-264] presents evidence from a single patient, WBN, to motivate a theory of lexical processing and representation in which syntactic information may be encoded and retrieved independently of semantic information. In his critique, Kemmerer argues that because Allen depended entirely on preposition-based verb subcategory violations to test WBN's knowledge of correct argument structure, his results, at best, address a "strawman" theory. This argument rests on the assumption that preposition subcategory options are superficial syntactic phenomena which are not represented by argument structure proper. We demonstrate that preposition subcategory is in fact treated as semantically determined argument structure in the theories that Allen evaluated, and thus far from irrelevant. In further discussion of grammatically relevant versus irrelevant semantic features, Kemmerer offers a review of his own studies. However, due to an important design shortcoming in these experiments, we remain unconvinced. Reemphasizing the fact the Allen (2005) never claimed to rule out all semantic contributions to syntax, we propose an improvement in Kemmerer's approach that might provide more satisfactory evidence on the distinction between the kinds of relevant versus irrelevant features his studies have addressed.
Constructing Adverse Outcome Pathways: a Demonstration of ...
Adverse outcome pathway (AOP) provides a conceptual framework to evaluate and integrate chemical toxicity and its effects across the levels of biological organization. As such, it is essential to develop a resource-efficient and effective approach to extend molecular initiating events (MIEs) of chemicals to their downstream phenotypes of a greater regulatory relevance. A number of ongoing public phenomics (high throughput phenotyping) efforts have been generating abundant phenotypic data annotated with ontology terms. These phenotypes can be analyzed semantically and linked to MIEs of interest, all in the context of a knowledge base integrated from a variety of ontologies for various species and knowledge domains. In such analyses, two phenotypic profiles (PPs; anchored by genes or diseases) each characterized by multiple ontology terms are compared for their semantic similarities within a common ontology graph, but across boundaries of species and knowledge domains. Taking advantage of publicly available ontologies and software tool kits, we have implemented an OS-Mapping (Ontology-based Semantics Mapping) approach as a Java application, and constructed a network of 19383 PPs as nodes with edges weighed by their pairwise semantic similarity scores. Individual PPs were assembled from public phenomics data. Out of possible 1.87×108 pairwise connections among these nodes, about 71% of them have similarity scores between 0.2 and the maximum possible of 1.0.
Jointly learning word embeddings using a corpus and a knowledge base
Bollegala, Danushka; Maehara, Takanori; Kawarabayashi, Ken-ichi
2018-01-01
Methods for representing the meaning of words in vector spaces purely using the information distributed in text corpora have proved to be very valuable in various text mining and natural language processing (NLP) tasks. However, these methods still disregard the valuable semantic relational structure between words in co-occurring contexts. These beneficial semantic relational structures are contained in manually-created knowledge bases (KBs) such as ontologies and semantic lexicons, where the meanings of words are represented by defining the various relationships that exist among those words. We combine the knowledge in both a corpus and a KB to learn better word embeddings. Specifically, we propose a joint word representation learning method that uses the knowledge in the KBs, and simultaneously predicts the co-occurrences of two words in a corpus context. In particular, we use the corpus to define our objective function subject to the relational constrains derived from the KB. We further utilise the corpus co-occurrence statistics to propose two novel approaches, Nearest Neighbour Expansion (NNE) and Hedged Nearest Neighbour Expansion (HNE), that dynamically expand the KB and therefore derive more constraints that guide the optimisation process. Our experimental results over a wide-range of benchmark tasks demonstrate that the proposed method statistically significantly improves the accuracy of the word embeddings learnt. It outperforms a corpus-only baseline and reports an improvement of a number of previously proposed methods that incorporate corpora and KBs in both semantic similarity prediction and word analogy detection tasks. PMID:29529052
Integrating reasoning and clinical archetypes using OWL ontologies and SWRL rules.
Lezcano, Leonardo; Sicilia, Miguel-Angel; Rodríguez-Solano, Carlos
2011-04-01
Semantic interoperability is essential to facilitate the computerized support for alerts, workflow management and evidence-based healthcare across heterogeneous electronic health record (EHR) systems. Clinical archetypes, which are formal definitions of specific clinical concepts defined as specializations of a generic reference (information) model, provide a mechanism to express data structures in a shared and interoperable way. However, currently available archetype languages do not provide direct support for mapping to formal ontologies and then exploiting reasoning on clinical knowledge, which are key ingredients of full semantic interoperability, as stated in the SemanticHEALTH report [1]. This paper reports on an approach to translate definitions expressed in the openEHR Archetype Definition Language (ADL) to a formal representation expressed using the Ontology Web Language (OWL). The formal representations are then integrated with rules expressed with Semantic Web Rule Language (SWRL) expressions, providing an approach to apply the SWRL rules to concrete instances of clinical data. Sharing the knowledge expressed in the form of rules is consistent with the philosophy of open sharing, encouraged by archetypes. Our approach also allows the reuse of formal knowledge, expressed through ontologies, and extends reuse to propositions of declarative knowledge, such as those encoded in clinical guidelines. This paper describes the ADL-to-OWL translation approach, describes the techniques to map archetypes to formal ontologies, and demonstrates how rules can be applied to the resulting representation. We provide examples taken from a patient safety alerting system to illustrate our approach. Copyright © 2010 Elsevier Inc. All rights reserved.
Semantic congruence reverses effects of sleep restriction on associative encoding.
Alberca-Reina, Esther; Cantero, Jose L; Atienza, Mercedes
2014-04-01
Encoding and memory consolidation are influenced by factors such as sleep and congruency of newly learned information with prior knowledge (i.e., schema). However, only a few studies have examined the contribution of sleep to enhancement of schema-dependent memory. Based on previous studies showing that total sleep deprivation specifically impairs hippocampal encoding, and that coherent schemas reduce the hippocampal consolidation period after learning, we predict that sleep loss in the pre-training night will mainly affect schema-unrelated information whereas sleep restriction in the post-training night will have similar effects on schema-related and unrelated information. Here, we tested this hypothesis by presenting participants with face-face associations that could be semantically related or unrelated under different sleep conditions: normal sleep before and after training, and acute sleep restriction either before or after training. Memory was tested one day after training, just after introducing an interference task, and two days later, without any interference. Significant results were evident on the second retesting session. In particular, sleep restriction before training enhanced memory for semantically congruent events in detriment of memory for unrelated events, supporting the specific role of sleep in hippocampal memory encoding. Unexpectedly, sleep restriction after training enhanced memory for both related and unrelated events. Although this finding may suggest a poorer encoding during the interference task, this hypothesis should be specifically tested in future experiments. All together, the present results support a framework in which encoding processes seem to be more vulnerable to sleep loss than consolidation processes. Copyright © 2014 Elsevier Inc. All rights reserved.
Learning to read words in a new language shapes the neural organization of the prior languages.
Mei, Leilei; Xue, Gui; Lu, Zhong-Lin; Chen, Chuansheng; Zhang, Mingxia; He, Qinghua; Wei, Miao; Dong, Qi
2014-12-01
Learning a new language entails interactions with one׳s prior language(s). Much research has shown how native language affects the cognitive and neural mechanisms of a new language, but little is known about whether and how learning a new language shapes the neural mechanisms of prior language(s). In two experiments in the current study, we used an artificial language training paradigm in combination with an fMRI to examine (1) the effects of different linguistic components (phonology and semantics) of a new language on the neural process of prior languages (i.e., native and second languages), and (2) whether such effects were modulated by the proficiency level in the new language. Results of Experiment 1 showed that when the training in a new language involved semantics (as opposed to only visual forms and phonology), neural activity during word reading in the native language (Chinese) was reduced in several reading-related regions, including the left pars opercularis, pars triangularis, bilateral inferior temporal gyrus, fusiform gyrus, and inferior occipital gyrus. Results of Experiment 2 replicated the results of Experiment 1 and further found that semantic training also affected neural activity during word reading in the subjects׳ second language (English). Furthermore, we found that the effects of the new language were modulated by the subjects׳ proficiency level in the new language. These results provide critical imaging evidence for the influence of learning to read words in a new language on word reading in native and second languages. Copyright © 2014 Elsevier Ltd. All rights reserved.
Children's and Adults' Abilities To Use Episodic and Semantic Information To Derive Inferences.
ERIC Educational Resources Information Center
Bourg, Tammy M.; And Others
A study investigated children's and adults' abilities to derive inferences requiring the integration of two episodic premises (episodic inferences) and inferences requiring the integration of one episodic premise with extra-stimulus, semantic knowledge. Subjects, 95 kindergarten, third grade, seventh grade, and college students, watched either an…
Event Congruency and Episodic Encoding: A Developmental fMRI Study
ERIC Educational Resources Information Center
Maril, Anat; Avital, Rinat; Reggev, Niv; Zuckerman, Maya; Sadeh, Talya; Sira, Liat Ben; Livneh, Neta
2011-01-01
A known contributor to adults' superior memory performance compared to children is their differential reliance on an existing knowledge base. Compared to those of adults, children's semantic networks are less accessible and less established, a difference that is also thought to contribute to children's relative resistance to semantically related…
ERIC Educational Resources Information Center
Hettiarachchi, Shyamani
2016-01-01
Background: Children diagnosed with intellectual difficulties experience difficulties with narrative skills, due to limited syntactic knowledge. The Colourful Semantics approach with thematic roles and a colour coding system may encourage syntactic development in children experiencing intellectual disabilities. Aim: To evaluate the effectiveness…
Semantic and Lexical Coherence.
ERIC Educational Resources Information Center
Fahnestock, Jeanne
Helping students understand coherence in terms of the lexical ties and semantic relations possible between clauses and sentences formalizes an area of writing instruction that has been somewhat vague before and makes the process of creating a coherent paragraph less mysterious. Many students do not have the intuitive knowledge base for absorbing…
Grounding Collaborative Learning in Semantics-Based Critiquing
ERIC Educational Resources Information Center
Cheung, William K.; Mørch, Anders I.; Wong, Kelvin C.; Lee, Cynthia; Liu, Jiming; Lam, Mason H.
2007-01-01
In this article we investigate the use of latent semantic analysis (LSA), critiquing systems, and knowledge building to support computer-based teaching of English composition. We have built and tested an English composition critiquing system that makes use of LSA to analyze student essays and compute feedback by comparing their essays with…
Development of Category-based Induction and Semantic Knowledge
ERIC Educational Resources Information Center
Fisher, Anna V.; Godwin, Karrie E.; Matlen, Bryan J.; Unger, Layla
2015-01-01
Category-based induction is a hallmark of mature cognition; however, little is known about its origins. This study evaluated the hypothesis that category-based induction is related to semantic development. Computational studies suggest that early on there is little differentiation among concepts, but learning and development lead to increased…
ERIC Educational Resources Information Center
Ohler, Jason
2008-01-01
The semantic web or Web 3.0 makes information more meaningful to people by making it more understandable to machines. In this article, the author examines the implications of Web 3.0 for education. The author considers three areas of impact: knowledge construction, personal learning network maintenance, and personal educational administration.…
Semantic Maps Capturing Organization Knowledge in e-Learning
NASA Astrophysics Data System (ADS)
Mavridis, Androklis; Koumpis, Adamantios; Demetriadis, Stavros N.
e-learning, shows much promise in accessibility and opportunity to learn, due to its asynchronous nature and its ability to transmit knowledge fast and effectively. However without a universal standard for online learning and teaching, many systems are proclaimed as “e-learning-compliant”, offering nothing more than automated services for delivering courses online, providing no additional enhancement to reusability and learner personalization. Hence, the focus is not on providing reusable and learner-centered content, but on developing the technology aspects of e-learning. This current trend has made it crucial to find a more refined definition of what constitutes knowledge in the e-learning context. We propose an e-learning system architecture that makes use of a knowledge model to facilitate continuous dialogue and inquiry-based knowledge learning, by exploiting the full benefits of the semantic web as a medium capable for supplying the web with formalized knowledge.
Mohammadhassanzadeh, Hossein; Van Woensel, William; Abidi, Samina Raza; Abidi, Syed Sibte Raza
2017-01-01
Capturing complete medical knowledge is challenging-often due to incomplete patient Electronic Health Records (EHR), but also because of valuable, tacit medical knowledge hidden away in physicians' experiences. To extend the coverage of incomplete medical knowledge-based systems beyond their deductive closure, and thus enhance their decision-support capabilities, we argue that innovative, multi-strategy reasoning approaches should be applied. In particular, plausible reasoning mechanisms apply patterns from human thought processes, such as generalization, similarity and interpolation, based on attributional, hierarchical, and relational knowledge. Plausible reasoning mechanisms include inductive reasoning , which generalizes the commonalities among the data to induce new rules, and analogical reasoning , which is guided by data similarities to infer new facts. By further leveraging rich, biomedical Semantic Web ontologies to represent medical knowledge, both known and tentative, we increase the accuracy and expressivity of plausible reasoning, and cope with issues such as data heterogeneity, inconsistency and interoperability. In this paper, we present a Semantic Web-based, multi-strategy reasoning approach, which integrates deductive and plausible reasoning and exploits Semantic Web technology to solve complex clinical decision support queries. We evaluated our system using a real-world medical dataset of patients with hepatitis, from which we randomly removed different percentages of data (5%, 10%, 15%, and 20%) to reflect scenarios with increasing amounts of incomplete medical knowledge. To increase the reliability of the results, we generated 5 independent datasets for each percentage of missing values, which resulted in 20 experimental datasets (in addition to the original dataset). The results show that plausibly inferred knowledge extends the coverage of the knowledge base by, on average, 2%, 7%, 12%, and 16% for datasets with, respectively, 5%, 10%, 15%, and 20% of missing values. This expansion in the KB coverage allowed solving complex disease diagnostic queries that were previously unresolvable, without losing the correctness of the answers. However, compared to deductive reasoning, data-intensive plausible reasoning mechanisms yield a significant performance overhead. We observed that plausible reasoning approaches, by generating tentative inferences and leveraging domain knowledge of experts, allow us to extend the coverage of medical knowledge bases, resulting in improved clinical decision support. Second, by leveraging OWL ontological knowledge, we are able to increase the expressivity and accuracy of plausible reasoning methods. Third, our approach is applicable to clinical decision support systems for a range of chronic diseases.
UBioLab: a web-LABoratory for Ubiquitous in-silico experiments.
Bartocci, E; Di Berardini, M R; Merelli, E; Vito, L
2012-03-01
The huge and dynamic amount of bioinformatic resources (e.g., data and tools) available nowadays in Internet represents a big challenge for biologists -for what concerns their management and visualization- and for bioinformaticians -for what concerns the possibility of rapidly creating and executing in-silico experiments involving resources and activities spread over the WWW hyperspace. Any framework aiming at integrating such resources as in a physical laboratory has imperatively to tackle -and possibly to handle in a transparent and uniform way- aspects concerning physical distribution, semantic heterogeneity, co-existence of different computational paradigms and, as a consequence, of different invocation interfaces (i.e., OGSA for Grid nodes, SOAP for Web Services, Java RMI for Java objects, etc.). The framework UBioLab has been just designed and developed as a prototype following the above objective. Several architectural features -as those ones of being fully Web-based and of combining domain ontologies, Semantic Web and workflow techniques- give evidence of an effort in such a direction. The integration of a semantic knowledge management system for distributed (bioinformatic) resources, a semantic-driven graphic environment for defining and monitoring ubiquitous workflows and an intelligent agent-based technology for their distributed execution allows UBioLab to be a semantic guide for bioinformaticians and biologists providing (i) a flexible environment for visualizing, organizing and inferring any (semantics and computational) "type" of domain knowledge (e.g., resources and activities, expressed in a declarative form), (ii) a powerful engine for defining and storing semantic-driven ubiquitous in-silico experiments on the domain hyperspace, as well as (iii) a transparent, automatic and distributed environment for correct experiment executions.
The semantic web in translational medicine: current applications and future directions
Machado, Catia M.; Rebholz-Schuhmann, Dietrich; Freitas, Ana T.; Couto, Francisco M.
2015-01-01
Semantic web technologies offer an approach to data integration and sharing, even for resources developed independently or broadly distributed across the web. This approach is particularly suitable for scientific domains that profit from large amounts of data that reside in the public domain and that have to be exploited in combination. Translational medicine is such a domain, which in addition has to integrate private data from the clinical domain with proprietary data from the pharmaceutical domain. In this survey, we present the results of our analysis of translational medicine solutions that follow a semantic web approach. We assessed these solutions in terms of their target medical use case; the resources covered to achieve their objectives; and their use of existing semantic web resources for the purposes of data sharing, data interoperability and knowledge discovery. The semantic web technologies seem to fulfill their role in facilitating the integration and exploration of data from disparate sources, but it is also clear that simply using them is not enough. It is fundamental to reuse resources, to define mappings between resources, to share data and knowledge. All these aspects allow the instantiation of translational medicine at the semantic web-scale, thus resulting in a network of solutions that can share resources for a faster transfer of new scientific results into the clinical practice. The envisioned network of translational medicine solutions is on its way, but it still requires resolving the challenges of sharing protected data and of integrating semantic-driven technologies into the clinical practice. PMID:24197933
The semantic web in translational medicine: current applications and future directions.
Machado, Catia M; Rebholz-Schuhmann, Dietrich; Freitas, Ana T; Couto, Francisco M
2015-01-01
Semantic web technologies offer an approach to data integration and sharing, even for resources developed independently or broadly distributed across the web. This approach is particularly suitable for scientific domains that profit from large amounts of data that reside in the public domain and that have to be exploited in combination. Translational medicine is such a domain, which in addition has to integrate private data from the clinical domain with proprietary data from the pharmaceutical domain. In this survey, we present the results of our analysis of translational medicine solutions that follow a semantic web approach. We assessed these solutions in terms of their target medical use case; the resources covered to achieve their objectives; and their use of existing semantic web resources for the purposes of data sharing, data interoperability and knowledge discovery. The semantic web technologies seem to fulfill their role in facilitating the integration and exploration of data from disparate sources, but it is also clear that simply using them is not enough. It is fundamental to reuse resources, to define mappings between resources, to share data and knowledge. All these aspects allow the instantiation of translational medicine at the semantic web-scale, thus resulting in a network of solutions that can share resources for a faster transfer of new scientific results into the clinical practice. The envisioned network of translational medicine solutions is on its way, but it still requires resolving the challenges of sharing protected data and of integrating semantic-driven technologies into the clinical practice. © The Author 2013. Published by Oxford University Press.
F-OWL: An Inference Engine for Semantic Web
NASA Technical Reports Server (NTRS)
Zou, Youyong; Finin, Tim; Chen, Harry
2004-01-01
Understanding and using the data and knowledge encoded in semantic web documents requires an inference engine. F-OWL is an inference engine for the semantic web language OWL language based on F-logic, an approach to defining frame-based systems in logic. F-OWL is implemented using XSB and Flora-2 and takes full advantage of their features. We describe how F-OWL computes ontology entailment and compare it with other description logic based approaches. We also describe TAGA, a trading agent environment that we have used as a test bed for F-OWL and to explore how multiagent systems can use semantic web concepts and technology.
Towards Semantic Modelling of Business Processes for Networked Enterprises
NASA Astrophysics Data System (ADS)
Furdík, Karol; Mach, Marián; Sabol, Tomáš
The paper presents an approach to the semantic modelling and annotation of business processes and information resources, as it was designed within the FP7 ICT EU project SPIKE to support creation and maintenance of short-term business alliances and networked enterprises. A methodology for the development of the resource ontology, as a shareable knowledge model for semantic description of business processes, is proposed. Systematically collected user requirements, conceptual models implied by the selected implementation platform as well as available ontology resources and standards are employed in the ontology creation. The process of semantic annotation is described and illustrated using an example taken from a real application case.
A familiar pattern? Semantic memory contributes to the enhancement of visuo-spatial memories.
Riby, Leigh M; Orme, Elizabeth
2013-03-01
In this study we quantify for the first time electrophysiological components associated with incorporating long-term semantic knowledge with visuo-spatial information using two variants of a traditional matrix patterns task. Results indicated that the matrix task with greater semantic content was associated with enhanced accuracy and RTs in a change-detection paradigm; this was also associated with increased P300 and N400 components as well as a sustained negative slow wave (NSW). In contrast, processing of the low semantic stimuli was associated with an increased N200 and a reduction in the P300. These findings suggest that semantic content can aid in reducing early visual processing of information and subsequent memory load by unitizing complex patterns into familiar forms. The N400/NSW may be associated with the requirements for maintaining visuo-spatial information about semantic forms such as orientation and relative location. Evidence for individual differences in semantic elaboration strategies used by participants is also discussed. Copyright © 2012 Elsevier Inc. All rights reserved.
Semantic Coherence Facilitates Distributional Learning.
Ouyang, Long; Boroditsky, Lera; Frank, Michael C
2017-04-01
Computational models have shown that purely statistical knowledge about words' linguistic contexts is sufficient to learn many properties of words, including syntactic and semantic category. For example, models can infer that "postman" and "mailman" are semantically similar because they have quantitatively similar patterns of association with other words (e.g., they both tend to occur with words like "deliver," "truck," "package"). In contrast to these computational results, artificial language learning experiments suggest that distributional statistics alone do not facilitate learning of linguistic categories. However, experiments in this paradigm expose participants to entirely novel words, whereas real language learners encounter input that contains some known words that are semantically organized. In three experiments, we show that (a) the presence of familiar semantic reference points facilitates distributional learning and (b) this effect crucially depends both on the presence of known words and the adherence of these known words to some semantic organization. Copyright © 2016 Cognitive Science Society, Inc.
Designing learning management system interoperability in semantic web
NASA Astrophysics Data System (ADS)
Anistyasari, Y.; Sarno, R.; Rochmawati, N.
2018-01-01
The extensive adoption of learning management system (LMS) has set the focus on the interoperability requirement. Interoperability is the ability of different computer systems, applications or services to communicate, share and exchange data, information, and knowledge in a precise, effective and consistent way. Semantic web technology and the use of ontologies are able to provide the required computational semantics and interoperability for the automation of tasks in LMS. The purpose of this study is to design learning management system interoperability in the semantic web which currently has not been investigated deeply. Moodle is utilized to design the interoperability. Several database tables of Moodle are enhanced and some features are added. The semantic web interoperability is provided by exploited ontology in content materials. The ontology is further utilized as a searching tool to match user’s queries and available courses. It is concluded that LMS interoperability in Semantic Web is possible to be performed.
Gibert, Karina; García-Rudolph, Alejandro; García-Molina, Alberto; Roig-Rovira, Teresa; Bernabeu, Montse; Tormos, José María
2008-01-01
Develop a classificatory tool to identify different populations of patients with Traumatic Brain Injury based on the characteristics of deficit and response to treatment. A KDD framework where first, descriptive statistics of every variable was done, data cleaning and selection of relevant variables. Then data was mined using a generalization of Clustering based on rules (CIBR), an hybrid AI and Statistics technique which combines inductive learning (AI) and clustering (Statistics). A prior Knowledge Base (KB) is considered to properly bias the clustering; semantic constraints implied by the KB hold in final clusters, guaranteeing interpretability of the resultis. A generalization (Exogenous Clustering based on rules, ECIBR) is presented, allowing to define the KB in terms of variables which will not be considered in the clustering process itself, to get more flexibility. Several tools as Class panel graph are introduced in the methodology to assist final interpretation. A set of 5 classes was recommended by the system and interpretation permitted profiles labeling. From the medical point of view, composition of classes is well corresponding with different patterns of increasing level of response to rehabilitation treatments. All the patients initially assessable conform a single group. Severe impaired patients are subdivided in four profiles which clearly distinct response patterns. Particularly interesting the partial response profile, where patients could not improve executive functions. Meaningful classes were obtained and, from a semantics point of view, the results were sensibly improved regarding classical clustering, according to our opinion that hybrid AI & Stats techniques are more powerful for KDD than pure ones.
Consolidation of Complex Events via Reinstatement in Posterior Cingulate Cortex.
Bird, Chris M; Keidel, James L; Ing, Leslie P; Horner, Aidan J; Burgess, Neil
2015-10-28
It is well-established that active rehearsal increases the efficacy of memory consolidation. It is also known that complex events are interpreted with reference to prior knowledge. However, comparatively little attention has been given to the neural underpinnings of these effects. In healthy adults humans, we investigated the impact of effortful, active rehearsal on memory for events by showing people several short video clips and then asking them to recall these clips, either aloud (Experiment 1) or silently while in an MRI scanner (Experiment 2). In both experiments, actively rehearsed clips were remembered in far greater detail than unrehearsed clips when tested a week later. In Experiment 1, highly similar descriptions of events were produced across retrieval trials, suggesting a degree of semanticization of the memories had taken place. In Experiment 2, spatial patterns of BOLD signal in medial temporal and posterior midline regions were correlated when encoding and rehearsing the same video. Moreover, the strength of this correlation in the posterior cingulate predicted the amount of information subsequently recalled. This is likely to reflect a strengthening of the representation of the video's content. We argue that these representations combine both new episodic information and stored semantic knowledge (or "schemas"). We therefore suggest that posterior midline structures aid consolidation by reinstating and strengthening the associations between episodic details and more generic schematic information. This leads to the creation of coherent memory representations of lifelike, complex events that are resistant to forgetting, but somewhat inflexible and semantic-like in nature. Copyright © 2015 Bird, Keidel et al.
Semantic networks based on titles of scientific papers
NASA Astrophysics Data System (ADS)
Pereira, H. B. B.; Fadigas, I. S.; Senna, V.; Moret, M. A.
2011-03-01
In this paper we study the topological structure of semantic networks based on titles of papers published in scientific journals. It discusses its properties and presents some reflections on how the use of social and complex network models can contribute to the diffusion of knowledge. The proposed method presented here is applied to scientific journals where the titles of papers are in English or in Portuguese. We show that the topology of studied semantic networks are small-world and scale-free.
How semantic category modulates preschool children's visual memory.
Giganti, Fiorenza; Viggiano, Maria Pia
2015-01-01
The dynamic interplay between perception and memory has been explored in preschool children by presenting filtered stimuli regarding animals and artifacts. The identification of filtered images was markedly influenced by both prior exposure and the semantic nature of the stimuli. The identification of animals required less physical information than artifacts did. Our results corroborate the notion that the human attention system evolves to reliably develop definite category-specific selection criteria by which living entities are monitored in different ways.
Chen, Xi; Chen, Huajun; Bi, Xuan; Gu, Peiqin; Chen, Jiaoyan; Wu, Zhaohui
2014-01-01
Understanding the functional mechanisms of the complex biological system as a whole is drawing more and more attention in global health care management. Traditional Chinese Medicine (TCM), essentially different from Western Medicine (WM), is gaining increasing attention due to its emphasis on individual wellness and natural herbal medicine, which satisfies the goal of integrative medicine. However, with the explosive growth of biomedical data on the Web, biomedical researchers are now confronted with the problem of large-scale data analysis and data query. Besides that, biomedical data also has a wide coverage which usually comes from multiple heterogeneous data sources and has different taxonomies, making it hard to integrate and query the big biomedical data. Embedded with domain knowledge from different disciplines all regarding human biological systems, the heterogeneous data repositories are implicitly connected by human expert knowledge. Traditional search engines cannot provide accurate and comprehensive search results for the semantically associated knowledge since they only support keywords-based searches. In this paper, we present BioTCM-SE, a semantic search engine for the information retrieval of modern biology and TCM, which provides biologists with a comprehensive and accurate associated knowledge query platform to greatly facilitate the implicit knowledge discovery between WM and TCM.
A concept ideation framework for medical device design.
Hagedorn, Thomas J; Grosse, Ian R; Krishnamurty, Sundar
2015-06-01
Medical device design is a challenging process, often requiring collaboration between medical and engineering domain experts. This collaboration can be best institutionalized through systematic knowledge transfer between the two domains coupled with effective knowledge management throughout the design innovation process. Toward this goal, we present the development of a semantic framework for medical device design that unifies a large medical ontology with detailed engineering functional models along with the repository of design innovation information contained in the US Patent Database. As part of our development, existing medical, engineering, and patent document ontologies were modified and interlinked to create a comprehensive medical device innovation and design tool with appropriate properties and semantic relations to facilitate knowledge capture, enrich existing knowledge, and enable effective knowledge reuse for different scenarios. The result is a Concept Ideation Framework for Medical Device Design (CIFMeDD). Key features of the resulting framework include function-based searching and automated inter-domain reasoning to uniquely enable identification of functionally similar procedures, tools, and inventions from multiple domains based on simple semantic searches. The significance and usefulness of the resulting framework for aiding in conceptual design and innovation in the medical realm are explored via two case studies examining medical device design problems. Copyright © 2015 Elsevier Inc. All rights reserved.
Chen, Xi; Chen, Huajun; Bi, Xuan; Gu, Peiqin; Chen, Jiaoyan; Wu, Zhaohui
2014-01-01
Understanding the functional mechanisms of the complex biological system as a whole is drawing more and more attention in global health care management. Traditional Chinese Medicine (TCM), essentially different from Western Medicine (WM), is gaining increasing attention due to its emphasis on individual wellness and natural herbal medicine, which satisfies the goal of integrative medicine. However, with the explosive growth of biomedical data on the Web, biomedical researchers are now confronted with the problem of large-scale data analysis and data query. Besides that, biomedical data also has a wide coverage which usually comes from multiple heterogeneous data sources and has different taxonomies, making it hard to integrate and query the big biomedical data. Embedded with domain knowledge from different disciplines all regarding human biological systems, the heterogeneous data repositories are implicitly connected by human expert knowledge. Traditional search engines cannot provide accurate and comprehensive search results for the semantically associated knowledge since they only support keywords-based searches. In this paper, we present BioTCM-SE, a semantic search engine for the information retrieval of modern biology and TCM, which provides biologists with a comprehensive and accurate associated knowledge query platform to greatly facilitate the implicit knowledge discovery between WM and TCM. PMID:24772189
Episodic memory, semantic memory, and amnesia.
Squire, L R; Zola, S M
1998-01-01
Episodic memory and semantic memory are two types of declarative memory. There have been two principal views about how this distinction might be reflected in the organization of memory functions in the brain. One view, that episodic memory and semantic memory are both dependent on the integrity of medial temporal lobe and midline diencephalic structures, predicts that amnesic patients with medial temporal lobe/diencephalic damage should be proportionately impaired in both episodic and semantic memory. An alternative view is that the capacity for semantic memory is spared, or partially spared, in amnesia relative to episodic memory ability. This article reviews two kinds of relevant data: 1) case studies where amnesia has occurred early in childhood, before much of an individual's semantic knowledge has been acquired, and 2) experimental studies with amnesic patients of fact and event learning, remembering and knowing, and remote memory. The data provide no compelling support for the view that episodic and semantic memory are affected differently in medial temporal lobe/diencephalic amnesia. However, episodic and semantic memory may be dissociable in those amnesic patients who additionally have severe frontal lobe damage.
Coronel, Jason C; Federmeier, Kara D
2016-04-01
There is growing recognition that some important forms of long-term memory are difficult to classify into one of the well-studied memory subtypes. One example is personal semantics. Like the episodes that are stored as part of one's autobiography, personal semantics is linked to an individual, yet, like general semantic memory, it is detached from a specific encoding context. Access to general semantics elicits an electrophysiological response known as the N400, which has been characterized across three decades of research; surprisingly, this response has not been fully examined in the context of personal semantics. In this study, we assessed responses to congruent and incongruent statements about people's own, personal preferences. We found that access to personal preferences elicited N400 responses, with congruency effects that were similar in latency and distribution to those for general semantic statements elicited from the same participants. These results suggest that the processing of personal and general semantics share important functional and neurobiological features. Copyright © 2016 Elsevier Ltd. All rights reserved.
Refining Automatically Extracted Knowledge Bases Using Crowdsourcing
Xian, Xuefeng; Cui, Zhiming
2017-01-01
Machine-constructed knowledge bases often contain noisy and inaccurate facts. There exists significant work in developing automated algorithms for knowledge base refinement. Automated approaches improve the quality of knowledge bases but are far from perfect. In this paper, we leverage crowdsourcing to improve the quality of automatically extracted knowledge bases. As human labelling is costly, an important research challenge is how we can use limited human resources to maximize the quality improvement for a knowledge base. To address this problem, we first introduce a concept of semantic constraints that can be used to detect potential errors and do inference among candidate facts. Then, based on semantic constraints, we propose rank-based and graph-based algorithms for crowdsourced knowledge refining, which judiciously select the most beneficial candidate facts to conduct crowdsourcing and prune unnecessary questions. Our experiments show that our method improves the quality of knowledge bases significantly and outperforms state-of-the-art automatic methods under a reasonable crowdsourcing cost. PMID:28588611
Developing an ontological explosion knowledge base for business continuity planning purposes.
Mohammadfam, Iraj; Kalatpour, Omid; Golmohammadi, Rostam; Khotanlou, Hasan
2013-01-01
Industrial accidents are among the most known challenges to business continuity. Many organisations have lost their reputation following devastating accidents. To manage the risks of such accidents, it is necessary to accumulate sufficient knowledge regarding their roots, causes and preventive techniques. The required knowledge might be obtained through various approaches, including databases. Unfortunately, many databases are hampered by (among other things) static data presentations, a lack of semantic features, and the inability to present accident knowledge as discrete domains. This paper proposes the use of Protégé software to develop a knowledge base for the domain of explosion accidents. Such a structure has a higher capability to improve information retrieval compared with common accident databases. To accomplish this goal, a knowledge management process model was followed. The ontological explosion knowledge base (EKB) was built for further applications, including process accident knowledge retrieval and risk management. The paper will show how the EKB has a semantic feature that enables users to overcome some of the search constraints of existing accident databases.
English Learners' Knowledge of Prepositions: Collocational Knowledge or Knowledge Based on Meaning?
ERIC Educational Resources Information Center
Mueller, Charles M.
2011-01-01
Second language (L2) learners' successful performance in an L2 can be partly attributed to their knowledge of collocations. In some cases, this knowledge is accompanied by knowledge of the semantic and/or grammatical patterns that motivate the collocation. At other times, collocational knowledge may serve a compensatory role. To determine the…
An Experiment in Scientific Program Understanding
NASA Technical Reports Server (NTRS)
Stewart, Mark E. M.; Owen, Karl (Technical Monitor)
2000-01-01
This paper concerns a procedure that analyzes aspects of the meaning or semantics of scientific and engineering code. This procedure involves taking a user's existing code, adding semantic declarations for some primitive variables, and parsing this annotated code using multiple, independent expert parsers. These semantic parsers encode domain knowledge and recognize formulae in different disciplines including physics, numerical methods, mathematics, and geometry. The parsers will automatically recognize and document some static, semantic concepts and help locate some program semantic errors. Results are shown for three intensively studied codes and seven blind test cases; all test cases are state of the art scientific codes. These techniques may apply to a wider range of scientific codes. If so, the techniques could reduce the time, risk, and effort required to develop and modify scientific codes.
iSMART: Ontology-based Semantic Query of CDA Documents
Liu, Shengping; Ni, Yuan; Mei, Jing; Li, Hanyu; Xie, Guotong; Hu, Gang; Liu, Haifeng; Hou, Xueqiao; Pan, Yue
2009-01-01
The Health Level 7 Clinical Document Architecture (CDA) is widely accepted as the format for electronic clinical document. With the rich ontological references in CDA documents, the ontology-based semantic query could be performed to retrieve CDA documents. In this paper, we present iSMART (interactive Semantic MedicAl Record reTrieval), a prototype system designed for ontology-based semantic query of CDA documents. The clinical information in CDA documents will be extracted into RDF triples by a declarative XML to RDF transformer. An ontology reasoner is developed to infer additional information by combining the background knowledge from SNOMED CT ontology. Then an RDF query engine is leveraged to enable the semantic queries. This system has been evaluated using the real clinical documents collected from a large hospital in southern China. PMID:20351883
Wu, Chia-Chien; Wang, Hsueh-Cheng; Pomplun, Marc
2014-12-01
A previous study (Vision Research 51 (2011) 1192-1205) found evidence for semantic guidance of visual attention during the inspection of real-world scenes, i.e., an influence of semantic relationships among scene objects on overt shifts of attention. In particular, the results revealed an observer bias toward gaze transitions between semantically similar objects. However, this effect is not necessarily indicative of semantic processing of individual objects but may be mediated by knowledge of the scene gist, which does not require object recognition, or by known spatial dependency among objects. To examine the mechanisms underlying semantic guidance, in the present study, participants were asked to view a series of displays with the scene gist excluded and spatial dependency varied. Our results show that spatial dependency among objects seems to be sufficient to induce semantic guidance. Scene gist, on the other hand, does not seem to affect how observers use semantic information to guide attention while viewing natural scenes. Extracting semantic information mainly based on spatial dependency may be an efficient strategy of the visual system that only adds little cognitive load to the viewing task. Copyright © 2014 Elsevier Ltd. All rights reserved.
Developing a kidney and urinary pathway knowledge base
2011-01-01
Background Chronic renal disease is a global health problem. The identification of suitable biomarkers could facilitate early detection and diagnosis and allow better understanding of the underlying pathology. One of the challenges in meeting this goal is the necessary integration of experimental results from multiple biological levels for further analysis by data mining. Data integration in the life science is still a struggle, and many groups are looking to the benefits promised by the Semantic Web for data integration. Results We present a Semantic Web approach to developing a knowledge base that integrates data from high-throughput experiments on kidney and urine. A specialised KUP ontology is used to tie the various layers together, whilst background knowledge from external databases is incorporated by conversion into RDF. Using SPARQL as a query mechanism, we are able to query for proteins expressed in urine and place these back into the context of genes expressed in regions of the kidney. Conclusions The KUPKB gives KUP biologists the means to ask queries across many resources in order to aggregate knowledge that is necessary for answering biological questions. The Semantic Web technologies we use, together with the background knowledge from the domain’s ontologies, allows both rapid conversion and integration of this knowledge base. The KUPKB is still relatively small, but questions remain about scalability, maintenance and availability of the knowledge itself. Availability The KUPKB may be accessed via http://www.e-lico.eu/kupkb. PMID:21624162
Form Overrides Meaning When Bilinguals Monitor for Errors
Ivanova, Iva; Ferreira, Victor S.; Gollan, Tamar H.
2016-01-01
Bilinguals rarely produce unintended language switches, which may in part be because switches are detected and corrected by an internal monitor. But are language switches easier or harder to detect than within-language semantic errors? To approximate internal monitoring, bilinguals listened (Experiment 1) or read aloud (Experiment 2) stories, and detected language switches (translation equivalents or semantically unrelated to expected words) and within-language errors (semantically related or unrelated to expected words). Bilinguals detected semantically related within-language errors most slowly and least accurately, language switches more quickly and accurately than within-language errors, and (in Experiment 2), translation equivalents as quickly and accurately as unrelated language switches. These results suggest that internal monitoring of form (which can detect mismatches in language membership) completes earlier than, and is independent of, monitoring of meaning. However, analysis of reading times prior to error detection revealed meaning violations to be more disruptive for processing than language violations. PMID:28649169
Speaker information affects false recognition of unstudied lexical-semantic associates.
Luthra, Sahil; Fox, Neal P; Blumstein, Sheila E
2018-05-01
Recognition of and memory for a spoken word can be facilitated by a prior presentation of that word spoken by the same talker. However, it is less clear whether this speaker congruency advantage generalizes to facilitate recognition of unheard related words. The present investigation employed a false memory paradigm to examine whether information about a speaker's identity in items heard by listeners could influence the recognition of novel items (critical intruders) phonologically or semantically related to the studied items. In Experiment 1, false recognition of semantically associated critical intruders was sensitive to speaker information, though only when subjects attended to talker identity during encoding. Results from Experiment 2 also provide some evidence that talker information affects the false recognition of critical intruders. Taken together, the present findings indicate that indexical information is able to contact the lexical-semantic network to affect the processing of unheard words.
Dynamic information processing states revealed through neurocognitive models of object semantics
Clarke, Alex
2015-01-01
Recognising objects relies on highly dynamic, interactive brain networks to process multiple aspects of object information. To fully understand how different forms of information about objects are represented and processed in the brain requires a neurocognitive account of visual object recognition that combines a detailed cognitive model of semantic knowledge with a neurobiological model of visual object processing. Here we ask how specific cognitive factors are instantiated in our mental processes and how they dynamically evolve over time. We suggest that coarse semantic information, based on generic shared semantic knowledge, is rapidly extracted from visual inputs and is sufficient to drive rapid category decisions. Subsequent recurrent neural activity between the anterior temporal lobe and posterior fusiform supports the formation of object-specific semantic representations – a conjunctive process primarily driven by the perirhinal cortex. These object-specific representations require the integration of shared and distinguishing object properties and support the unique recognition of objects. We conclude that a valuable way of understanding the cognitive activity of the brain is though testing the relationship between specific cognitive measures and dynamic neural activity. This kind of approach allows us to move towards uncovering the information processing states of the brain and how they evolve over time. PMID:25745632
A common type system for clinical natural language processing
2013-01-01
Background One challenge in reusing clinical data stored in electronic medical records is that these data are heterogenous. Clinical Natural Language Processing (NLP) plays an important role in transforming information in clinical text to a standard representation that is comparable and interoperable. Information may be processed and shared when a type system specifies the allowable data structures. Therefore, we aim to define a common type system for clinical NLP that enables interoperability between structured and unstructured data generated in different clinical settings. Results We describe a common type system for clinical NLP that has an end target of deep semantics based on Clinical Element Models (CEMs), thus interoperating with structured data and accommodating diverse NLP approaches. The type system has been implemented in UIMA (Unstructured Information Management Architecture) and is fully functional in a popular open-source clinical NLP system, cTAKES (clinical Text Analysis and Knowledge Extraction System) versions 2.0 and later. Conclusions We have created a type system that targets deep semantics, thereby allowing for NLP systems to encapsulate knowledge from text and share it alongside heterogenous clinical data sources. Rather than surface semantics that are typically the end product of NLP algorithms, CEM-based semantics explicitly build in deep clinical semantics as the point of interoperability with more structured data types. PMID:23286462
Spatio-Temporal Change Modeling of Lulc: a Semantic Kriging Approach
NASA Astrophysics Data System (ADS)
Bhattacharjee, S.; Ghosh, S. K.
2015-07-01
Spatio-temporal land-use/ land-cover (LULC) change modeling is important to forecast the future LULC distribution, which may facilitate natural resource management, urban planning, etc. The spatio-temporal change in LULC trend often exhibits non-linear behavior, due to various dynamic factors, such as, human intervention (e.g., urbanization), environmental factors, etc. Hence, proper forecasting of LULC distribution should involve the study and trend modeling of historical data. Existing literatures have reported that the meteorological attributes (e.g., NDVI, LST, MSI), are semantically related to the terrain. Being influenced by the terrestrial dynamics, the temporal changes of these attributes depend on the LULC properties. Hence, incorporating meteorological knowledge into the temporal prediction process may help in developing an accurate forecasting model. This work attempts to study the change in inter-annual LULC pattern and the distribution of different meteorological attributes of a region in Kolkata (a metropolitan city in India) during the years 2000-2010 and forecast the future spread of LULC using semantic kriging (SemK) approach. A new variant of time-series SemK is proposed, namely Rev-SemKts to capture the multivariate semantic associations between different attributes. From empirical analysis, it may be observed that the augmentation of semantic knowledge in spatio-temporal modeling of meteorological attributes facilitate more precise forecasting of LULC pattern.
A common type system for clinical natural language processing.
Wu, Stephen T; Kaggal, Vinod C; Dligach, Dmitriy; Masanz, James J; Chen, Pei; Becker, Lee; Chapman, Wendy W; Savova, Guergana K; Liu, Hongfang; Chute, Christopher G
2013-01-03
One challenge in reusing clinical data stored in electronic medical records is that these data are heterogenous. Clinical Natural Language Processing (NLP) plays an important role in transforming information in clinical text to a standard representation that is comparable and interoperable. Information may be processed and shared when a type system specifies the allowable data structures. Therefore, we aim to define a common type system for clinical NLP that enables interoperability between structured and unstructured data generated in different clinical settings. We describe a common type system for clinical NLP that has an end target of deep semantics based on Clinical Element Models (CEMs), thus interoperating with structured data and accommodating diverse NLP approaches. The type system has been implemented in UIMA (Unstructured Information Management Architecture) and is fully functional in a popular open-source clinical NLP system, cTAKES (clinical Text Analysis and Knowledge Extraction System) versions 2.0 and later. We have created a type system that targets deep semantics, thereby allowing for NLP systems to encapsulate knowledge from text and share it alongside heterogenous clinical data sources. Rather than surface semantics that are typically the end product of NLP algorithms, CEM-based semantics explicitly build in deep clinical semantics as the point of interoperability with more structured data types.
Naming of objects, faces and buildings in mild cognitive impairment.
Ahmed, Samrah; Arnold, Robert; Thompson, Sian A; Graham, Kim S; Hodges, John R
2008-06-01
Accruing evidence suggests that the cognitive deficits in very early Alzheimer's Disease (AD) are not confined to episodic memory, with a number of studies documenting semantic memory deficits, especially for knowledge of people. To investigate whether this difficulty in naming famous people extends to other proper names based information, three naming tasks - the Graded Naming Test (GNT), which uses objects and animals, the Graded Faces Test (GFT) and the newly designed Graded Buildings Test (GBT) - were administered to 69 participants (32 patients in the early prodromal stage of AD, so-called Mild Cognitive Impairment (MCI), and 37 normal control participants). Patients were found to be impaired on all three tests compared to controls, although naming of objects was significantly better than naming of faces and buildings. Discriminant analysis successfully predicted group membership for 100% controls and 78.1% of patients. The results suggest that even in cases that do not yet fulfil criteria for AD naming of famous people and buildings is impaired, and that both these semantic domains show greater vulnerability than general semantic knowledge. A semantic deficit together with the hallmark episodic deficit may be common in MCI, and that the use of graded tasks tapping semantic memory may be useful for the early identification of patients with MCI.
Integrated Semantics Service Platform for the Internet of Things: A Case Study of a Smart Office
Ryu, Minwoo; Kim, Jaeho; Yun, Jaeseok
2015-01-01
The Internet of Things (IoT) allows machines and devices in the world to connect with each other and generate a huge amount of data, which has a great potential to provide useful knowledge across service domains. Combining the context of IoT with semantic technologies, we can build integrated semantic systems to support semantic interoperability. In this paper, we propose an integrated semantic service platform (ISSP) to support ontological models in various IoT-based service domains of a smart city. In particular, we address three main problems for providing integrated semantic services together with IoT systems: semantic discovery, dynamic semantic representation, and semantic data repository for IoT resources. To show the feasibility of the ISSP, we develop a prototype service for a smart office using the ISSP, which can provide a preset, personalized office environment by interpreting user text input via a smartphone. We also discuss a scenario to show how the ISSP-based method would help build a smart city, where services in each service domain can discover and exploit IoT resources that are wanted across domains. We expect that our method could eventually contribute to providing people in a smart city with more integrated, comprehensive services based on semantic interoperability. PMID:25608216
Integrated semantics service platform for the Internet of Things: a case study of a smart office.
Ryu, Minwoo; Kim, Jaeho; Yun, Jaeseok
2015-01-19
The Internet of Things (IoT) allows machines and devices in the world to connect with each other and generate a huge amount of data, which has a great potential to provide useful knowledge across service domains. Combining the context of IoT with semantic technologies, we can build integrated semantic systems to support semantic interoperability. In this paper, we propose an integrated semantic service platform (ISSP) to support ontological models in various IoT-based service domains of a smart city. In particular, we address three main problems for providing integrated semantic services together with IoT systems: semantic discovery, dynamic semantic representation, and semantic data repository for IoT resources. To show the feasibility of the ISSP, we develop a prototype service for a smart office using the ISSP, which can provide a preset, personalized office environment by interpreting user text input via a smartphone. We also discuss a scenario to show how the ISSP-based method would help build a smart city, where services in each service domain can discover and exploit IoT resources that are wanted across domains. We expect that our method could eventually contribute to providing people in a smart city with more integrated, comprehensive services based on semantic interoperability.
Thematic relatedness production norms for 100 object concepts.
Jouravlev, Olessia; McRae, Ken
2016-12-01
Knowledge of thematic relations is an area of increased interest in semantic memory research because it is crucial to many cognitive processes. One methodological issue that researchers face is how to identify pairs of thematically related concepts that are well-established in semantic memory for most people. In this article, we review existing methods of assessing thematic relatedness and provide thematic relatedness production norming data for 100 object concepts. In addition, 1,174 related concept pairs obtained from the production norms were classified as reflecting one of the five subtypes of relations: attributive, argument, coordinate, locative, and temporal. The database and methodology will be useful for researchers interested in the effects of thematic knowledge on language processing, analogical reasoning, similarity judgments, and memory. These data will also benefit researchers interested in investigating potential processing differences among the five types of semantic relations.
Episodic and Semantic Memory: Implications for the Role of Emotion in Advertising.
ERIC Educational Resources Information Center
Thorson, Esther
In an examination of the way people store and retrieve information from advertising, this paper draws a distinction between "semantic" memory, which stores general knowledge about the world, and "episodic" memory, which stores information about specific events. It then argues that episodic memory plays a more significant role…
The Development of Semantic Knowledge Systems for Realistic Goals.
ERIC Educational Resources Information Center
Goldman, Susan R.
This study investigates age differences in children's semantic expectations regarding causal relations in stories about three realistic goal situations (being friendly, getting a dog, and doing chores). Twenty children at each of three age levels (ages 6, 9, and 12) were asked to produce stories and answer probe questions about wanting and not…
Towards a Semantic E-Learning Theory by Using a Modelling Approach
ERIC Educational Resources Information Center
Yli-Luoma, Pertti V. J.; Naeve, Ambjorn
2006-01-01
In the present study, a semantic perspective on e-learning theory is advanced and a modelling approach is used. This modelling approach towards the new learning theory is based on the four SECI phases of knowledge conversion: Socialisation, Externalisation, Combination and Internalisation, introduced by Nonaka in 1994, and involving two levels of…
A Cybernetic Approach To Study the Learnability of the LOGO Turtle World.
ERIC Educational Resources Information Center
Ippel, Martin J.; Meulemans, Caroline J. M.
1998-01-01
This study of second- and third-grade students in the Netherlands tests the hypothesis that simplification of the semantic structure will facilitate semantic understanding and acquisition of syntax knowledge within the LOGO Turtle World. Two microworlds were designed applying the theory of automata and abstract languages. (Author/LRW)
Semantic Social Network Portal for Collaborative Online Communities
ERIC Educational Resources Information Center
Neumann, Marco; O'Murchu, Ina; Breslin, John; Decker, Stefan; Hogan, Deirdre; MacDonaill, Ciaran
2005-01-01
Purpose: The motivation for this investigation is to apply social networking features to a semantic network portal, which supports the efforts in enterprise training units to up-skill the employee in the company, and facilitates the creation and reuse of knowledge in online communities. Design/methodology/approach: The paper provides an overview…
ERIC Educational Resources Information Center
Huettig, Falk; McQueen, James M.
2007-01-01
Experiments 1 and 2 examined the time-course of retrieval of phonological, visual-shape and semantic knowledge as Dutch participants listened to sentences and looked at displays of four pictures. Given a sentence with "beker," "beaker," for example, the display contained phonological (a beaver, "bever"), shape (a…
Semantics of User Interface for Image Retrieval: Possibility Theory and Learning Techniques.
ERIC Educational Resources Information Center
Crehange, M.; And Others
1989-01-01
Discusses the need for a rich semantics for the user interface in interactive image retrieval and presents two methods for building such interfaces: possibility theory applied to fuzzy data retrieval, and a machine learning technique applied to learning the user's deep need. Prototypes developed using videodisks and knowledge-based software are…
Supporting Student Research with Semantic Technologies and Digital Archives
ERIC Educational Resources Information Center
Martinez-Garcia, Agustina; Corti, Louise
2012-01-01
This article discusses how the idea of higher education students as producers of knowledge rather than consumers can be operationalised by means of student research projects, in which processes of research archiving and analysis are enabled through the use of semantic technologies. It discusses how existing digital repository frameworks can be…
Sleep Increases Explicit Solutions and Reduces Intuitive Judgments of Semantic Coherence
ERIC Educational Resources Information Center
Zander, Thea; Volz, Kirsten G.; Born, Jan; Diekelmann, Susanne
2017-01-01
Sleep fosters the generation of explicit knowledge. Whether sleep also benefits implicit intuitive decisions about underlying patterns is unclear. We examined sleep's role in explicit and intuitive semantic coherence judgments. Participants encoded sets of three words and after a sleep or wake period were required to judge the potential…
Item-Specific and Generalization Effects on Brain Activation when Learning Chinese Characters
ERIC Educational Resources Information Center
Deng, Yuan; Booth, James R.; Chou, Tai-Li; Ding, Guo-Sheng; Peng, Dan-Ling
2008-01-01
Neural changes related to learning of the meaning of Chinese characters in English speakers were examined using functional magnetic resonance imaging (fMRI). We examined item specific learning effects for trained characters, but also the generalization of semantic knowledge to novel transfer characters that shared a semantic radical (part of a…
MENTOR: an enabler for interoperable intelligent systems
NASA Astrophysics Data System (ADS)
Sarraipa, João; Jardim-Goncalves, Ricardo; Steiger-Garcao, Adolfo
2010-07-01
A community with knowledge organisation based on ontologies will enable an increase in the computational intelligence of its information systems. However, due to the worldwide diversity of communities, a high number of knowledge representation elements, which are not semantically coincident, have appeared representing the same segment of reality, becoming a barrier to business communications. Even if a domain community uses the same kind of technologies in its information systems, such as ontologies, it doesn't solve its semantics differences. In order to solve this interoperability problem, a solution is to use a reference ontology as an intermediary in the communications between the community enterprises and the outside, while allowing the enterprises to keep their own ontology and semantics unchanged internally. This work proposes MENTOR, a methodology to support the development of a common reference ontology for a group of organisations sharing the same business domain. This methodology is based on the mediator ontology (MO) concept, which assists the semantic transformations among each enterprise's ontology and the referential one. The MO enables each organisation to keep its own terminology, glossary and ontological structures, while providing seamless communication and interaction with the others.
Leveraging Semantic Knowledge in IRB Databases to Improve Translation Science
Hurdle, John F.; Botkin, Jeffery; Rindflesch, Thomas C.
2007-01-01
We introduce the notion that research administrative databases (RADs), such as those increasingly used to manage information flow in the Institutional Review Board (IRB), offer a novel, useful, and mine-able data source overlooked by informaticists. As a proof of concept, using an IRB database we extracted all titles and abstracts from system startup through January 2007 (n=1,876); formatted these in a pseudo-MEDLINE format; and processed them through the SemRep semantic knowledge extraction system. Even though SemRep is tuned to find semantic relations in MEDLINE citations, we found that it performed comparably well on the IRB texts. When adjusted to eliminate non-healthcare IRB submissions (e.g., economic and education studies), SemRep extracted an average of 7.3 semantic relations per IRB abstract (compared to an average of 11.1 for MEDLINE citations) with a precision of 70% (compared to 78% for MEDLINE). We conclude that RADs, as represented by IRB data, are mine-able with existing tools, but that performance will improve as these tools are tuned for RAD structures. PMID:18693856
Word add-in for ontology recognition: semantic enrichment of scientific literature.
Fink, J Lynn; Fernicola, Pablo; Chandran, Rahul; Parastatidis, Savas; Wade, Alex; Naim, Oscar; Quinn, Gregory B; Bourne, Philip E
2010-02-24
In the current era of scientific research, efficient communication of information is paramount. As such, the nature of scholarly and scientific communication is changing; cyberinfrastructure is now absolutely necessary and new media are allowing information and knowledge to be more interactive and immediate. One approach to making knowledge more accessible is the addition of machine-readable semantic data to scholarly articles. The Word add-in presented here will assist authors in this effort by automatically recognizing and highlighting words or phrases that are likely information-rich, allowing authors to associate semantic data with those words or phrases, and to embed that data in the document as XML. The add-in and source code are publicly available at http://www.codeplex.com/UCSDBioLit. The Word add-in for ontology term recognition makes it possible for an author to add semantic data to a document as it is being written and it encodes these data using XML tags that are effectively a standard in life sciences literature. Allowing authors to mark-up their own work will help increase the amount and quality of machine-readable literature metadata.
Pantazatos, Spiro P.; Li, Jianrong; Pavlidis, Paul; Lussier, Yves A.
2009-01-01
An approach towards heterogeneous neuroscience dataset integration is proposed that uses Natural Language Processing (NLP) and a knowledge-based phenotype organizer system (PhenOS) to link ontology-anchored terms to underlying data from each database, and then maps these terms based on a computable model of disease (SNOMED CT®). The approach was implemented using sample datasets from fMRIDC, GEO, The Whole Brain Atlas and Neuronames, and allowed for complex queries such as “List all disorders with a finding site of brain region X, and then find the semantically related references in all participating databases based on the ontological model of the disease or its anatomical and morphological attributes”. Precision of the NLP-derived coding of the unstructured phenotypes in each dataset was 88% (n = 50), and precision of the semantic mapping between these terms across datasets was 98% (n = 100). To our knowledge, this is the first example of the use of both semantic decomposition of disease relationships and hierarchical information found in ontologies to integrate heterogeneous phenotypes across clinical and molecular datasets. PMID:20495688
Semantic layers for illustrative volume rendering.
Rautek, Peter; Bruckner, Stefan; Gröller, Eduard
2007-01-01
Direct volume rendering techniques map volumetric attributes (e.g., density, gradient magnitude, etc.) to visual styles. Commonly this mapping is specified by a transfer function. The specification of transfer functions is a complex task and requires expert knowledge about the underlying rendering technique. In the case of multiple volumetric attributes and multiple visual styles the specification of the multi-dimensional transfer function becomes more challenging and non-intuitive. We present a novel methodology for the specification of a mapping from several volumetric attributes to multiple illustrative visual styles. We introduce semantic layers that allow a domain expert to specify the mapping in the natural language of the domain. A semantic layer defines the mapping of volumetric attributes to one visual style. Volumetric attributes and visual styles are represented as fuzzy sets. The mapping is specified by rules that are evaluated with fuzzy logic arithmetics. The user specifies the fuzzy sets and the rules without special knowledge about the underlying rendering technique. Semantic layers allow for a linguistic specification of the mapping from attributes to visual styles replacing the traditional transfer function specification.
Numeracy Skills in Patients With Degenerative Disorders and Focal Brain Lesions
Cappelletti, Marinella; Butterworth, Brian; Kopelman, Michael
2012-01-01
Objective: To characterize the numerical profile of patients with acquired brain disorders. Method: We investigated numeracy skills in 76 participants—40 healthy controls and 36 patients with neurodegenerative disorders (Alzheimer dementia, frontotemporal dementia, semantic dementia, progressive aphasia) and with focal brain lesions affecting parietal, frontal, and temporal areas as in herpes simplex encephalitis (HSE). All patients were tested with the same comprehensive battery of paper-and-pencil and computerized tasks assessing numerical abilities and calculation. Degenerative and HSE patients also performed nonnumerical semantic tasks. Results: Our results, based on nonparametric group statistics as well as on the analysis of individual patients, and all highly significant, show that: (a) all patients, including those with parietal lesions—a key brain area for numeracy processing—had intact processing of number quantity; (b) patients with impaired semantic knowledge had much better preserved numerical knowledge; and (c) most patients showed impaired calculation skills, with the exception of most semantic dementia and HSE patients. Conclusion: Our results allow us, for the first time, to characterize the numeracy skills in patients with a variety of neurological conditions and to suggest that the pattern of numerical performance can vary considerably across different neurological populations. Moreover, the selective sparing of calculation skills in most semantic dementia and HSE suggest that numerical abilities are an independent component of the semantic system. Finally, our data suggest that, besides the parietal areas, other brain regions might be critical to the understanding and processing of numerical concepts. PMID:22122516
A scale-based connected coherence tree algorithm for image segmentation.
Ding, Jundi; Ma, Runing; Chen, Songcan
2008-02-01
This paper presents a connected coherence tree algorithm (CCTA) for image segmentation with no prior knowledge. It aims to find regions of semantic coherence based on the proposed epsilon-neighbor coherence segmentation criterion. More specifically, with an adaptive spatial scale and an appropriate intensity-difference scale, CCTA often achieves several sets of coherent neighboring pixels which maximize the probability of being a single image content (including kinds of complex backgrounds). In practice, each set of coherent neighboring pixels corresponds to a coherence class (CC). The fact that each CC just contains a single equivalence class (EC) ensures the separability of an arbitrary image theoretically. In addition, the resultant CCs are represented by tree-based data structures, named connected coherence tree (CCT)s. In this sense, CCTA is a graph-based image analysis algorithm, which expresses three advantages: 1) its fundamental idea, epsilon-neighbor coherence segmentation criterion, is easy to interpret and comprehend; 2) it is efficient due to a linear computational complexity in the number of image pixels; 3) both subjective comparisons and objective evaluation have shown that it is effective for the tasks of semantic object segmentation and figure-ground separation in a wide variety of images. Those images either contain tiny, long and thin objects or are severely degraded by noise, uneven lighting, occlusion, poor illumination, and shadow.
Automatic information extraction from unstructured mammography reports using distributed semantics.
Gupta, Anupama; Banerjee, Imon; Rubin, Daniel L
2018-02-01
To date, the methods developed for automated extraction of information from radiology reports are mainly rule-based or dictionary-based, and, therefore, require substantial manual effort to build these systems. Recent efforts to develop automated systems for entity detection have been undertaken, but little work has been done to automatically extract relations and their associated named entities in narrative radiology reports that have comparable accuracy to rule-based methods. Our goal is to extract relations in a unsupervised way from radiology reports without specifying prior domain knowledge. We propose a hybrid approach for information extraction that combines dependency-based parse tree with distributed semantics for generating structured information frames about particular findings/abnormalities from the free-text mammography reports. The proposed IE system obtains a F 1 -score of 0.94 in terms of completeness of the content in the information frames, which outperforms a state-of-the-art rule-based system in this domain by a significant margin. The proposed system can be leveraged in a variety of applications, such as decision support and information retrieval, and may also easily scale to other radiology domains, since there is no need to tune the system with hand-crafted information extraction rules. Copyright © 2018 Elsevier Inc. All rights reserved.
Gainotti, Guido; Ciaraffa, Francesca; Silveri, Maria Caterina; Marra, Camillo
2009-11-01
According to the "sensory-motor model of semantic knowledge," different categories of knowledge differ for the weight that different "sources of knowledge" have in their representation. Our study aimed to evaluate this model, checking if subjective evaluations given by normal subjects confirm the different weight that various sources of knowledge have in the representation of different biological and artifact categories and of unique entities, such as famous people or monuments. Results showed that the visual properties are considered as the main source of knowledge for all the living and nonliving categories (as well as for unique entities), but that the clustering of these "sources of knowledge" is different for biological and artifacts categories. Visual data are, indeed, mainly associated with other perceptual (auditory, olfactory, gustatory, and tactual) attributes in the mental representation of living beings and unique entities, whereas they are associated with action-related properties and tactile information in the case of artifacts.
Hippocampal activation during retrieval of spatial context from episodic and semantic memory.
Hoscheidt, Siobhan M; Nadel, Lynn; Payne, Jessica; Ryan, Lee
2010-10-15
The hippocampus, a region implicated in the processing of spatial information and episodic memory, is central to the debate concerning the relationship between episodic and semantic memory. Studies of medial temporal lobe amnesic patients provide evidence that the hippocampus is critical for the retrieval of episodic but not semantic memory. On the other hand, recent neuroimaging studies of intact individuals report hippocampal activation during retrieval of both autobiographical memories and semantic information that includes historical facts, famous faces, and categorical information, suggesting that episodic and semantic memory may engage the hippocampus during memory retrieval in similar ways. Few studies have matched episodic and semantic tasks for the degree to which they include spatial content, even though spatial content may be what drives hippocampal activation during semantic retrieval. To examine this issue, we conducted a functional magnetic resonance imaging (fMRI) study in which retrieval of spatial and nonspatial information was compared during an episodic and semantic recognition task. Results show that the hippocampus (1) participates preferentially in the retrieval of episodic memories; (2) is also engaged by retrieval of semantic memories, particularly those that include spatial information. These data suggest that sharp dissociations between episodic and semantic memory may be overly simplistic and that the hippocampus plays a role in the retrieval of spatial content whether drawn from a memory of one's own life experiences or real-world semantic knowledge. Published by Elsevier B.V.
Semantic eScience for Ecosystem Understanding and Monitoring: The Jefferson Project Case Study
NASA Astrophysics Data System (ADS)
McGuinness, D. L.; Pinheiro da Silva, P.; Patton, E. W.; Chastain, K.
2014-12-01
Monitoring and understanding ecosystems such as lakes and their watersheds is becoming increasingly important. Accelerated eutrophication threatens our drinking water sources. Many believe that the use of nutrients (e.g., road salts, fertilizers, etc.) near these sources may have negative impacts on animal and plant populations and water quality although it is unclear how to best balance broad community needs. The Jefferson Project is a joint effort between RPI, IBM and the Fund for Lake George aimed at creating an instrumented water ecosystem along with an appropriate cyberinfrastructure that can serve as a global model for ecosystem monitoring, exploration, understanding, and prediction. One goal is to help communities understand the potential impacts of actions such as road salting strategies so that they can make appropriate informed recommendations that serve broad community needs. Our semantic eScience team is creating a semantic infrastructure to support data integration and analysis to help trained scientists as well as the general public to better understand the lake today, and explore potential future scenarios. We are leveraging our RPI Tetherless World Semantic Web methodology that provides an agile process for describing use cases, identification of appropriate background ontologies and technologies, implementation, and evaluation. IBM is providing a state-of-the-art sensor network infrastructure along with a collection of tools to share, maintain, analyze and visualize the network data. In the context of this sensor infrastructure, we will discuss our semantic approach's contributions in three knowledge representation and reasoning areas: (a) human interventions on the deployment and maintenance of local sensor networks including the scientific knowledge to decide how and where sensors are deployed; (b) integration, interpretation and management of data coming from external sources used to complement the project's models; and (c) knowledge about simulation results including parameters, interpretation of results, and comparison of results against external data. We will also demonstrate some example queries highlighting the benefits of our semantic approach and will also identify reusable components.
Laiacona, M; Barbarotto, R; Capitani, E
1993-12-01
We report two head-injured patients whose knowledge of living things was selectively disrupted. Their semantic knowledge was tested with naming and verbal comprehension tasks and a verbal questionnaire. In all of them there was consistent evidence that knowledge of living things was impaired and that of non-living things was relatively preserved. The living things deficit emerged irrespective of whether the question tapped associative or perceptual knowledge or required visual or non visual information. In all tasks the category effect was still significant after the influence on the performance of the following variables was partialled out: word frequency, concept familiarity, prototypicality, name agreement, image agreement and visual complexity. In the verbal questionnaire dissociations were still significant even after adjustment for the difficulty of questions for normals, that had proven greater for living things. Besides diffuse brain damage, both patients presented with a left posterior temporo-parietal lesion.
Interdependence of episodic and semantic memory: evidence from neuropsychology.
Greenberg, Daniel L; Verfaellie, Mieke
2010-09-01
Tulving's (1972) theory of memory draws a distinction between general knowledge (semantic memory) and memory for events (episodic memory). Neuropsychological studies have generally examined each type of memory in isolation, but theorists have long argued that these two forms of memory are interdependent. Here we review several lines of neuropsychological research that have explored the interdependence of episodic and semantic memory. The studies show that these forms of memory can affect each other both at encoding and at retrieval. We suggest that theories of memory should be revised to account for all of the interdependencies between episodic and semantic memory; they should also incorporate forms of memory that do not fit neatly into either category.
Interdependence of episodic and semantic memory: Evidence from neuropsychology
GREENBERG, DANIEL L.; VERFAELLIE, MIEKE
2010-01-01
Tulving's (1972) theory of memory draws a distinction between general knowledge (semantic memory) and memory for events (episodic memory). Neuropsychological studies have generally examined each type of memory in isolation, but theorists have long argued that these two forms of memory are interdependent. Here we review several lines of neuropsychological research that have explored the interdependence of episodic and semantic memory. The studies show that these forms of memory can affect each other both at encoding and at retrieval. We suggest that theories of memory should be revised to account for all of the interdependencies between episodic and semantic memory; they should also incorporate forms of memory that do not fit neatly into either category. PMID:20561378
Cohen, Trevor; Schvaneveldt, Roger W; Rindflesch, Thomas C
2009-11-14
Corpus-derived distributional models of semantic distance between terms have proved useful in a number of applications. For both theoretical and practical reasons, it is desirable to extend these models to encode discrete concepts and the ways in which they are related to one another. In this paper, we present a novel vector space model that encodes semantic predications derived from MEDLINE by the SemRep system into a compact spatial representation. The associations captured by this method are of a different and complementary nature to those derived by traditional vector space models, and the encoding of predication types presents new possibilities for knowledge discovery and information retrieval.
Accessing world knowledge: evidence from N400 and reaction time priming.
Chwilla, Dorothee J; Kolk, Herman H J
2005-12-01
How fast are we in accessing world knowledge? In two experiments, we tested for priming for word triplets that described a conceptual script (e.g., DIRECTOR-BRIBE-DISMISSAL) but were not associatively related and did not share a category relationship. Event-related brain potentials were used to track the time course at which script information becomes available. In Experiment 1, in which participants made lexical decisions, we found a facilitation for script-related relative to unrelated triplets, as indicated by (i) a decrease in both reaction time and errors, and (ii) an N400-like priming effect. In Experiment 2, we further explored the locus of script priming by increasing the contribution of meaning integration processes. The participants' task was to indicate whether the three words presented a plausible scenario. Again, an N400 script priming effect was obtained. Directing attention to script relations was effective in enhancing the N400 effect. The time course of the N400 effect was similar to that of the standard N400 effect to semantic relations. The present results show that script priming can be obtained in the visual modality, and that script information is immediately accessed and integrated with context. This supports the view that script information forms a central aspect of word meaning. The RT and N400 script priming effects reported in this article are problematic for most current semantic priming models, like spreading activation models, expectancy models, and task-specific semantic matching/integration models. They support a view in which there is no clear cutoff point between semantic knowledge and world knowledge.
Semantic similarity between ontologies at different scales
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Qingpeng; Haglin, David J.
In the past decade, existing and new knowledge and datasets has been encoded in different ontologies for semantic web and biomedical research. The size of ontologies is often very large in terms of number of concepts and relationships, which makes the analysis of ontologies and the represented knowledge graph computational and time consuming. As the ontologies of various semantic web and biomedical applications usually show explicit hierarchical structures, it is interesting to explore the trade-offs between ontological scales and preservation/precision of results when we analyze ontologies. This paper presents the first effort of examining the capability of this idea viamore » studying the relationship between scaling biomedical ontologies at different levels and the semantic similarity values. We evaluate the semantic similarity between three Gene Ontology slims (Plant, Yeast, and Candida, among which the latter two belong to the same kingdom—Fungi) using four popular measures commonly applied to biomedical ontologies (Resnik, Lin, Jiang-Conrath, and SimRel). The results of this study demonstrate that with proper selection of scaling levels and similarity measures, we can significantly reduce the size of ontologies without losing substantial detail. In particular, the performance of Jiang-Conrath and Lin are more reliable and stable than that of the other two in this experiment, as proven by (a) consistently showing that Yeast and Candida are more similar (as compared to Plant) at different scales, and (b) small deviations of the similarity values after excluding a majority of nodes from several lower scales. This study provides a deeper understanding of the application of semantic similarity to biomedical ontologies, and shed light on how to choose appropriate semantic similarity measures for biomedical engineering.« less
UBioLab: a web-laboratory for ubiquitous in-silico experiments.
Bartocci, Ezio; Cacciagrano, Diletta; Di Berardini, Maria Rita; Merelli, Emanuela; Vito, Leonardo
2012-07-09
The huge and dynamic amount of bioinformatic resources (e.g., data and tools) available nowadays in Internet represents a big challenge for biologists –for what concerns their management and visualization– and for bioinformaticians –for what concerns the possibility of rapidly creating and executing in-silico experiments involving resources and activities spread over the WWW hyperspace. Any framework aiming at integrating such resources as in a physical laboratory has imperatively to tackle –and possibly to handle in a transparent and uniform way– aspects concerning physical distribution, semantic heterogeneity, co-existence of different computational paradigms and, as a consequence, of different invocation interfaces (i.e., OGSA for Grid nodes, SOAP for Web Services, Java RMI for Java objects, etc.). The framework UBioLab has been just designed and developed as a prototype following the above objective. Several architectural features –as those ones of being fully Web-based and of combining domain ontologies, Semantic Web and workflow techniques– give evidence of an effort in such a direction. The integration of a semantic knowledge management system for distributed (bioinformatic) resources, a semantic-driven graphic environment for defining and monitoring ubiquitous workflows and an intelligent agent-based technology for their distributed execution allows UBioLab to be a semantic guide for bioinformaticians and biologists providing (i) a flexible environment for visualizing, organizing and inferring any (semantics and computational) "type" of domain knowledge (e.g., resources and activities, expressed in a declarative form), (ii) a powerful engine for defining and storing semantic-driven ubiquitous in-silico experiments on the domain hyperspace, as well as (iii) a transparent, automatic and distributed environment for correct experiment executions.
Pobric, Gorana; Lambon Ralph, Matthew A.; Jefferies, Elizabeth
2009-01-01
Conceptual knowledge allows us to bring meaning to our world. Studies of semantic dementia (SD) patients and some functional neuroimaging studies indicate that the anterior temporal lobes, bilaterally, are a core neural substrate for the formation of conceptual representations. The majority of SD patients (who have circumscribed atrophy of the anterior temporal lobes) have better comprehension of concrete than abstract words. However, this finding remains controversial, as some individual SD patients have exhibited reverse imageability effects, i.e., relative preservation of abstract knowledge. This would imply that the anterior temporal lobes are particularly crucial for processing sensory aspects of semantic knowledge, which are an important part of concrete but not abstract concepts. To adjudicate on this debate, we used offline, low-frequency, repetitive transcranial magnetic stimulation to disrupt neural processing temporarily in the left or right temporal poles (TPs). We examined this effect using a synonym judgement task, comprising high, medium and low imageability items, which we have previously employed with a case-series of SD patients. The time required to make semantic decisions was slowed considerably, particularly for low imageability items, consistent with the pattern we observed in SD. These results confirm that both TPs make a critical contribution to semantic processing, even for abstract concepts that do not have strong sensory representations. PMID:19303592
VuWiki: An Ontology-Based Semantic Wiki for Vulnerability Assessments
NASA Astrophysics Data System (ADS)
Khazai, Bijan; Kunz-Plapp, Tina; Büscher, Christian; Wegner, Antje
2014-05-01
The concept of vulnerability, as well as its implementation in vulnerability assessments, is used in various disciplines and contexts ranging from disaster management and reduction to ecology, public health or climate change and adaptation, and a corresponding multitude of ideas about how to conceptualize and measure vulnerability exists. Three decades of research in vulnerability have generated a complex and growing body of knowledge that challenges newcomers, practitioners and even experienced researchers. To provide a structured representation of the knowledge field "vulnerability assessment", we have set up an ontology-based semantic wiki for reviewing and representing vulnerability assessments: VuWiki, www.vuwiki.org. Based on a survey of 55 vulnerability assessment studies, we first developed an ontology as an explicit reference system for describing vulnerability assessments. We developed the ontology in a theoretically controlled manner based on general systems theory and guided by principles for ontology development in the field of earth and environment (Raskin and Pan 2005). Four key questions form the first level "branches" or categories of the developed ontology: (1) Vulnerability of what? (2) Vulnerability to what? (3) What reference framework was used in the vulnerability assessment?, and (4) What methodological approach was used in the vulnerability assessment? These questions correspond to the basic, abstract structure of the knowledge domain of vulnerability assessments and have been deduced from theories and concepts of various disciplines. The ontology was then implemented in a semantic wiki which allows for the classification and annotation of vulnerability assessments. As a semantic wiki, VuWiki does not aim at "synthesizing" a holistic and overarching model of vulnerability. Instead, it provides both scientists and practitioners with a uniform ontology as a reference system and offers easy and structured access to the knowledge field of vulnerability assessments with the possibility for any user to retrieve assessments using specific research criteria. Furthermore, Vuwiki can serve as a collaborative knowledge platform that allows for the active participation of those generating and using the knowledge represented in the wiki.
Knowledge Evolution in Distributed Geoscience Datasets and the Role of Semantic Technologies
NASA Astrophysics Data System (ADS)
Ma, X.
2014-12-01
Knowledge evolves in geoscience, and the evolution is reflected in datasets. In a context with distributed data sources, the evolution of knowledge may cause considerable challenges to data management and re-use. For example, a short news published in 2009 (Mascarelli, 2009) revealed the geoscience community's concern that the International Commission on Stratigraphy's change to the definition of Quaternary may bring heavy reworking of geologic maps. Now we are in the era of the World Wide Web, and geoscience knowledge is increasingly modeled and encoded in the form of ontologies and vocabularies by using semantic technologies. Accordingly, knowledge evolution leads to a consequence called ontology dynamics. Flouris et al. (2008) summarized 10 topics of general ontology changes/dynamics such as: ontology mapping, morphism, evolution, debugging and versioning, etc. Ontology dynamics makes impacts at several stages of a data life cycle and causes challenges, such as: the request for reworking of the extant data in a data center, semantic mismatch among data sources, differentiated understanding of a same piece of dataset between data providers and data users, as well as error propagation in cross-discipline data discovery and re-use (Ma et al., 2014). This presentation will analyze the best practices in the geoscience community so far and summarize a few recommendations to reduce the negative impacts of ontology dynamics in a data life cycle, including: communities of practice and collaboration on ontology and vocabulary building, link data records to standardized terms, and methods for (semi-)automatic reworking of datasets using semantic technologies. References: Flouris, G., Manakanatas, D., Kondylakis, H., Plexousakis, D., Antoniou, G., 2008. Ontology change: classification and survey. The Knowledge Engineering Review 23 (2), 117-152. Ma, X., Fox, P., Rozell, E., West, P., Zednik, S., 2014. Ontology dynamics in a data life cycle: Challenges and recommendations from a Geoscience Perspective. Journal of Earth Science 25 (2), 407-412. Mascarelli, A.L., 2009. Quaternary geologists win timescale vote. Nature 459, 624.
Soshi, Takahiro; Nakajima, Heizo; Hagiwara, Hiroko
2016-10-01
Static knowledge about the grammar of a natural language is represented in the cortico-subcortical system. However, the differences in dynamic verbal processing under different cognitive conditions are unclear. To clarify this, we conducted an electrophysiological experiment involving a semantic priming paradigm in which semantically congruent or incongruent word sequences (prime nouns-target verbs) were randomly presented. We examined the event-related brain potentials that occurred in response to congruent and incongruent target words that were preceded by primes with or without grammatical case markers. The two participant groups performed either the shallow (lexical judgment) or deep (direct semantic judgment) semantic tasks. We hypothesized that, irrespective of the case markers, the congruent targets would reduce centro-posterior N400 activities under the deep semantic condition, which induces selective attention to the semantic relatedness of content words. However, the same congruent targets with correct case markers would reduce lateralized negativity under the shallow semantic condition because grammatical case markers are related to automatic structural integration under semantically unattended conditions. We observed that congruent targets (e.g., 'open') that were preceded by primes with congruent case markers (e.g., 'shutter-object case') reduced lateralized negativity under the shallow semantic condition. In contrast, congruent targets, irrespective of case markers, consistently yielded N400 reductions under the deep semantic condition. To summarize, human neural verbal processing differed in response to the same grammatical markers in the same verbal expressions under semantically attended or unattended conditions.
Zhu, Zude; Yang, Fengjun; Li, Dongning; Zhou, Lianjun; Liu, Ying; Zhang, Ying; Chen, Xuezhi
2017-01-01
While aging is associated with increased knowledge, it is also associated with decreased semantic integration. To investigate brain activation changes during semantic integration, a sample of forty-eight 25-75 year-old adults read sentences with high cloze (HC) and low cloze (LC) probability while functional magnetic resonance imaging was conducted. Significant age-related reduction of cloze effect (LC vs. HC) was found in several regions, especially the left middle frontal gyrus (MFG) and right inferior frontal gyrus (IFG), which play an important role in semantic integration. Moreover, when accounting for global gray matter volume reduction, the age-cloze correlation in the left MFG and right IFG was absent. The results suggest that brain structural atrophy may disrupt brain response in aging brains, which then show less brain engagement in semantic integration.
Bobb, Susan C; Mani, Nivedita
2013-06-01
The current study investigated the interaction of implicit grammatical gender and semantic category knowledge during object identification. German-learning toddlers (24-month-olds) were presented with picture pairs and heard a noun (without a preceding article) labeling one of the pictures. Labels for target and distracter images either matched or mismatched in grammatical gender and either matched or mismatched in semantic category. When target and distracter overlapped in both semantic and gender information, target recognition was impaired compared with when target and distracter overlapped on only one dimension. Results suggest that by 24 months of age, German-learning toddlers are already forming not only semantic but also grammatical gender categories and that these sources of information are activated, and interact, during object identification. Copyright © 2013 Elsevier Inc. All rights reserved.
Utilizing Linked Open Data Sources for Automatic Generation of Semantic Metadata
NASA Astrophysics Data System (ADS)
Nummiaho, Antti; Vainikainen, Sari; Melin, Magnus
In this paper we present an application that can be used to automatically generate semantic metadata for tags given as simple keywords. The application that we have implemented in Java programming language creates the semantic metadata by linking the tags to concepts in different semantic knowledge bases (CrunchBase, DBpedia, Freebase, KOKO, Opencyc, Umbel and/or WordNet). The steps that our application takes in doing so include detecting possible languages, finding spelling suggestions and finding meanings from amongst the proper nouns and common nouns separately. Currently, our application supports English, Finnish and Swedish words, but other languages could be included easily if the required lexical tools (spellcheckers, etc.) are available. The created semantic metadata can be of great use in, e.g., finding and combining similar contents, creating recommendations and targeting advertisements.